2024
Wang, Z., Veličković, P., Hennes, D., Tomašev, N., Prince, L., Kaisers, M., . . . Tuyls, K. (2024). TacticAI: an AI assistant for football tactics.. Nature communications, 15(1), 1906. doi:10.1038/s41467-024-45965-xDOI: 10.1038/s41467-024-45965-x
2022
Omidshafiei, S., Hennes, D., Garnelo, M., Wang, Z., Recasens, A., Tarassov, E., . . . Tuyls, K. (2022). Multiagent off-screen behavior prediction in football. SCIENTIFIC REPORTS, 12(1). doi:10.1038/s41598-022-12547-0DOI: 10.1038/s41598-022-12547-0
Generative Models over Neural Controllers for Transfer Learning (Chapter)
Butterworth, J., Savani, R., & Tuyls, K. (2022). Generative Models over Neural Controllers for Transfer Learning. In Unknown Book (Vol. 13398, pp. 400-413). doi:10.1007/978-3-031-14714-2_28DOI: 10.1007/978-3-031-14714-2_28
2021
Piliouras, G., Rowland, M., Omidshafiei, S., Elie, R., Hennes, D., Connor, J., & Tuyls, K. (2021). Evolutionary Dynamics and $Φ$-Regret Minimization in Games. Retrieved from http://arxiv.org/abs/2106.14668v1
2020
Tuyls, K., Omidshafiei, S., Muller, P., Wang, Z., Connor, J., Hennes, D., . . . Hassabis, D. (2021). Game Plan: What AI can do for Football, and What Football can do for AI. JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH, 71, 41-88. Retrieved from https://www.webofscience.com/
Navigating the landscape of multiplayer games (Journal article)
Omidshafiei, S., Tuyls, K., Czarnecki, W. M., Santos, F. C., Rowland, M., Connor, J., . . . Munos, R. (2020). Navigating the landscape of multiplayer games. NATURE COMMUNICATIONS, 11(1). doi:10.1038/s41467-020-19244-4DOI: 10.1038/s41467-020-19244-4
Czarnecki, W. M., Gidel, G., Tracey, B., Tuyls, K., Omidshafiei, S., Balduzzi, D., & Jaderberg, M. (2020). Real World Games Look Like Spinning Tops. Retrieved from http://arxiv.org/abs/2004.09468v2
Tuyls, K., Perolat, J., Lanctot, M., Hughes, E., Everett, R., Leibo, J. Z., . . . Graepel, T. (2020). Bounds and dynamics for empirical game theoretic analysis. AUTONOMOUS AGENTS AND MULTI-AGENT SYSTEMS, 34(1). doi:10.1007/s10458-019-09432-yDOI: 10.1007/s10458-019-09432-y
Palmer, G., Schnieders, B., Savani, R., Tuyls, K., Fossel, J., & Flore, H. (2020). The Automated Inspection of Opaque Liquid Vaccines. In ECAI 2020: 24TH EUROPEAN CONFERENCE ON ARTIFICIAL INTELLIGENCE Vol. 325 (pp. 1898-1905). doi:10.3233/FAIA200307DOI: 10.3233/FAIA200307
Fast computation of nash equilibria in imperfect information games (Conference Paper)
Munos, R., Perolat, J., Lespiau, J. B., Rowland, M., de Vylder, B., Lanctot, M., . . . Tuyls, K. (2020). Fast computation of nash equilibria in imperfect information games. In 37th International Conference on Machine Learning, ICML 2020 Vol. PartF168147-10 (pp. 7076-7086).
Fine-tuning Deep RL with Gradient-Free Optimization (Conference Paper)
de Bruin, T., Kober, J., Tuyls, K., & Babuska, R. (2020). Fine-tuning Deep RL with Gradient-Free Optimization. In IFAC PAPERSONLINE Vol. 53 (pp. 8049-8056). doi:10.1016/j.ifacol.2020.12.2240DOI: 10.1016/j.ifacol.2020.12.2240
Learning robust policies when losing control (Conference Paper)
Klima, R., Bloembergen, D., Kaisers, M., & Tuyls, K. (2020). Learning robust policies when losing control. In ALA 2018 - Adaptive Learning Agents - Workshop at the Federated AI Meeting 2018.
Learning robust policies when losing control (Conference Paper)
Klima, R., Bloembergen, D., Kaisers, M., & Tuyls, K. (2020). Learning robust policies when losing control. In ALA 2018 - Adaptive Learning Agents - Workshop at the Federated AI Meeting 2018.
Neural replicator dynamics: Multiagent learning via hedging policy gradients (Conference Paper)
Hennes, D., Morrill, D., Omidshafiei, S., Munos, R., Perolat, J., Lanctot, M., . . . Tuyls, K. (2020). Neural replicator dynamics: Multiagent learning via hedging policy gradients. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS Vol. 2020-May (pp. 492-501).
Stability of Cooperation in Societies of Emotional and Moody Agents (Conference Paper)
Collenette, J., Atkinson, K., Bloembergen, D., & Tuyls, K. (2019). Stability of Cooperation in Societies of Emotional and Moody Agents. In ALIFE 2019: THE 2019 CONFERENCE ON ARTIFICIAL LIFE (pp. 467-474). Retrieved from https://www.webofscience.com/
2019
Distant supervision of relation extraction in sparse data (Journal article)
Ranjbar-Sahraei, B., Rahmani, H., Weiss, G., & Tuyls, K. (2019). Distant supervision of relation extraction in sparse data. INTELLIGENT DATA ANALYSIS, 23(5), 1145-1166. doi:10.3233/IDA-184238DOI: 10.3233/IDA-184238
Minimal navigation solution for a swarm of tiny flying robots to explore an unknown environment (Journal article)
McGuire, K. N., De Wagter, C., Tuyls, K., Kappen, H. J., & de Croon, G. C. H. E. (2019). Minimal navigation solution for a swarm of tiny flying robots to explore an unknown environment. SCIENCE ROBOTICS, 4(35). doi:10.1126/scirobotics.aaw9710DOI: 10.1126/scirobotics.aaw9710
Multiagent Evaluation under Incomplete Information (Journal article)
Rowland, M., Omidshafiei, S., Tuyls, K., Perolat, J., Valko, M., Piliouras, G., & Munos, R. (2019). Multiagent Evaluation under Incomplete Information. ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 32 (NIPS 2019), 32. Retrieved from https://www.webofscience.com/
Omidshafiei, S., Papadimitriou, C., Piliouras, G., Tuyls, K., Rowland, M., Lespiau, J. -B., . . . Munos, R. (2019). α-Rank: Multi-Agent Evaluation by Evolution. SCIENTIFIC REPORTS, 9. doi:10.1038/s41598-019-45619-9DOI: 10.1038/s41598-019-45619-9
Evolving indoor navigational strategies using gated recurrent units in NEAT (Conference Paper)
Butterworth, J., Savani, R., & Tuyls, K. (2019). Evolving indoor navigational strategies using gated recurrent units in NEAT. In GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion (pp. 111-112). doi:10.1145/3319619.3321995DOI: 10.1145/3319619.3321995
Lockhart, E., Lanctot, M., Pérolat, J., Lespiau, J. -B., Morrill, D., Timbers, F., & Tuyls, K. (2019). Computing Approximate Equilibria in Sequential Adversarial Games by Exploitability Descent. Retrieved from http://arxiv.org/abs/1903.05614v4
Fully Convolutional One-Shot Object Segmentation for Industrial Robotics (Conference Paper)
Schnieders, B., Luo, S., Palmer, G., & Tuyls, K. (2019). Fully Convolutional One-Shot Object Segmentation for Industrial Robotics. In AAMAS '19: PROCEEDINGS OF THE 18TH INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS AND MULTIAGENT SYSTEMS (pp. 1161-1169). Retrieved from https://www.webofscience.com/
Difierentiable game mechanics (Journal article)
Letcher, A., Balduzzi, D., Racaniére, S., Martens, J., Foerster, J., Tuyls, K., & Graepel, T. (2019). Difierentiable game mechanics. Journal of Machine Learning Research, 20.
Klima, R., Bloembergen, D., Kaisers, M., & Tuyls, K. (2019). Robust Temporal Difference Learning for Critical Domains. AAMAS '19: PROCEEDINGS OF THE 18TH INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS AND MULTIAGENT SYSTEMS, 350-358. Retrieved from https://www.webofscience.com/
Deep reinforcement learning with relational inductive biases (Conference Paper)
Zambaldi, V., Raposo, D., Santoro, A., Bapst, V., Li, Y., Babuschkin, I., . . . Battaglia, P. (2019). Deep reinforcement learning with relational inductive biases. In 7th International Conference on Learning Representations, ICLR 2019.
Deep reinforcement learning with relational inductive biases (Conference Paper)
Zambaldi, V., Raposo, D., Santoro, A., Bapst, V., Li, Y., Babuschkin, I., . . . Battaglia, P. (2019). Deep reinforcement learning with relational inductive biases. In 7th International Conference on Learning Representations, ICLR 2019.
Deep reinforcement learning with relational inductive biases (Conference Paper)
Zambaldi, V., Raposo, D., Santoro, A., Bapst, V., Li, Y., Babuschkin, I., . . . Battaglia, P. (2019). Deep reinforcement learning with relational inductive biases. In 7th International Conference on Learning Representations, ICLR 2019.
Collenette, J., Atkinson, K., Bloembergen, D., & Tuyls, K. (2019). Stability of Human-Inspired Agent Societies. In AAMAS '19: PROCEEDINGS OF THE 18TH INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS AND MULTIAGENT SYSTEMS (pp. 1889-1891). Retrieved from https://www.webofscience.com/
2018
Srinivasan, S., Lanctot, M., Zambaldi, V., Perolat, J., Tuyls, K., Munos, R., & Bowling, M. (2018). Actor-Critic Policy Optimization in Partially Observable Multiagent Environments. ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 31 (NIPS 2018), 31. Retrieved from http://gateway.webofknowledge.com/
Hughes, E., Leibo, J. Z., Phillips, M., Tuyls, K., Duenez-Guzman, E., Castaneda, A. G., . . . Graepel, T. (2018). Inequity aversion improves cooperation in intertemporal social dilemmas. ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 31 (NIPS 2018), 31. Retrieved from http://gateway.webofknowledge.com/
Multi robot collision avoidance in a shared workspace (Journal article)
Claes, D., & Tuyls, K. (2018). Multi robot collision avoidance in a shared workspace. AUTONOMOUS ROBOTS, 42(8), 1749-1770. doi:10.1007/s10514-018-9726-5DOI: 10.1007/s10514-018-9726-5
Multiagent learning paradigms (Conference Paper)
Tuyls, K., & Stone, P. (2018). Multiagent learning paradigms. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 10767 LNAI (pp. 3-21). doi:10.1007/978-3-030-01713-2_1DOI: 10.1007/978-3-030-01713-2_1
Distance-based multi-robot coordination on pocket drones (Conference Paper)
Broecker, B., Tuyls, K., Butterworth, J., & IEEE. (2018). Distance-based multi-robot coordination on pocket drones. In 2018 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA) (pp. 6389-6394). Retrieved from http://gateway.webofknowledge.com/
Palmer, G., Savani, R., & Tuyls, K. (2019). Negative Update Intervals in Deep Multi-Agent Reinforcement Learning. In AAMAS '19: PROCEEDINGS OF THE 18TH INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS AND MULTIAGENT SYSTEMS (pp. 43-51). Retrieved from https://www.webofscience.com/
McGuire, K. N., de Croon, G. C. H. E., & Tuyls, K. (2019). A comparative study of bug algorithms for robot navigation. ROBOTICS AND AUTONOMOUS SYSTEMS, 121. doi:10.1016/j.robot.2019.103261DOI: 10.1016/j.robot.2019.103261
de Bruin, T., Kober, J., Tuyls, K., & Babuska, R. (2018). Experience Selection in Deep Reinforcement Learning for Control. JOURNAL OF MACHINE LEARNING RESEARCH, 19. Retrieved from https://www.webofscience.com/
Collenette, J., Atkinson, K. M., Bloembergen, D., & Tuyls, K. (2018). On the role of mobility and interaction topologies in social dilemmas. In Proceedings of the artificial life conference 2018 Vol. 30 (pp. 477-484). Tokyo, Japan: MIT Press. Retrieved from https://www.mitpressjournals.org/doi/abs/10.1162/isal_a_00088
Zhang, C., Li, X., Hao, J., Chen, S., Tuyls, K., Feng, Z., . . . Chen, R. (2018). SCC-rFMQ Learning in Cooperative Markov Games with Continuous Actions. In AAMAS 2018. Stockholm, Sweden. Retrieved from http://ifaamas.org/Proceedings/aamas2018/pdfs/p2162.pdf
Value-decomposition networks for cooperative multi-agent learning based on team reward (Conference Paper)
Sunehag, P., Lever, G., Gruslys, A., Czarnecki, W. M., Zambaldi, V., Jaderberg, M., . . . Graepel, T. (2018). Value-decomposition networks for cooperative multi-agent learning based on team reward. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS Vol. 3 (pp. 2085-2087).
Balduzzi, D., Tuyls, K., Perolat, J., & Graepel, T. (2018). Re-evaluating Evaluation. ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 31 (NIPS 2018), 31. Retrieved from https://www.webofscience.com/
Klima, R., Bloembergen, D., Savani, R., Tuyls, K., Wittig, A., Sapera, A., & Izzo, D. (2018). Space Debris Removal: Learning to Cooperate and the Price of Anarchy. Frontiers in Robotics and AI, 5. doi:10.3389/frobt.2018.00054DOI: 10.3389/frobt.2018.00054
Lazaridou, A., Hermann, K. M., Tuyls, K., & Clark, S. (2018). Emergence of Linguistic Communication from Referential Games with Symbolic and Pixel Input. Retrieved from http://arxiv.org/abs/1804.03984v1
Cao, K., Lazaridou, A., Lanctot, M., Leibo, J. Z., Tuyls, K., & Clark, S. (2018). Emergent Communication through Negotiation. Retrieved from http://arxiv.org/abs/1804.03980v1
A Generalised Method for Empirical Game Theoretic Analysis (Journal article)
Tuyls, K., Perolat, J., Lanctot, M., Leibo, J. Z., & Graepel, T. (2018). A Generalised Method for Empirical Game Theoretic Analysis. PROCEEDINGS OF THE 17TH INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS AND MULTIAGENT SYSTEMS (AAMAS' 18), 77-85. Retrieved from https://www.webofscience.com/
Atkinson, K. M., Collenette, J., Bloembergen, D., & Tuyls, K. (2018). Modelling mood in co-operative emotional agents. In 13th International Symposium on Distributed Autonomous Robotic Systems 2016. London.
SA-IGA: a multiagent reinforcement learning method towards socially optimal outcomes (Journal article)
Zhang, C., Li, X., Hao, J., Chen, S., Tuyls, K., Xue, W., & Feng, Z. (2019). SA-IGA: a multiagent reinforcement learning method towards socially optimal outcomes. AUTONOMOUS AGENTS AND MULTI-AGENT SYSTEMS, 33(4), 403-429. doi:10.1007/s10458-019-09411-3DOI: 10.1007/s10458-019-09411-3
Balduzzi, D., Racaniere, S., Martens, J., Foerster, J., Tuyls, K., & Graepel, T. (2018). The Mechanics of <i>n</i>-Player Differentiable Games. In INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 80 Vol. 80. Retrieved from https://www.webofscience.com/
Integrating State Representation Learning Into Deep Reinforcement Learning (Journal article)
de Bruin, T., Kober, J., Tuyls, K., & Babuska, R. (2018). Integrating State Representation Learning Into Deep Reinforcement Learning. IEEE Robotics and Automation Letters, 3(3), 1394-1401. doi:10.1109/lra.2018.2800101DOI: 10.1109/lra.2018.2800101
Tuyls, K., Perolat, J., Lanctot, M., Ostrovski, G., Savani, R., Leibo, J., . . . Legg, S. (2018). Symmetric Decomposition of Asymmetric Games. Scientific Reports, 8. doi:10.1038/s41598-018-19194-4DOI: 10.1038/s41598-018-19194-4
Emergence of linguistic communication from referential games with symbolic and pixel input (Conference Paper)
Lazaridou, A., Hermann, K. M., Tuyls, K., & Clark, S. (2018). Emergence of linguistic communication from referential games with symbolic and pixel input. In 6th International Conference on Learning Representations, ICLR 2018 - Conference Track Proceedings.
Emergent communication through negotiation (Conference Paper)
Cao, K., Lazaridou, A., Lanctot, M., Leibo, J. Z., Tuyls, K., & Clark, S. (2018). Emergent communication through negotiation. In 6th International Conference on Learning Representations, ICLR 2018 - Conference Track Proceedings.
Reports on the 2018 AAAI Spring Symposium Series (Journal article)
Amato, C., Ammar, H. B., Churchill, E., Karpas, E., Kido, T., Kuniavsky, M., . . . Zhang, S. (2018). Reports on the 2018 AAAI Spring Symposium Series. AI MAGAZINE, 39(4), 29-35. doi:10.1609/aimag.v39i4.2824DOI: 10.1609/aimag.v39i4.2824
2017
NOctoSLAM: Fast Octree Surface Normal Mapping and Registration (Conference Paper)
Fossel, J., Tuyls, K., Schnieders, B., Claes, D., & Hennes, D. (2017). NOctoSLAM: Fast Octree Surface Normal Mapping and Registration. In 2017 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS) (pp. 6764-6769). Retrieved from http://gateway.webofknowledge.com/
Lanctot, M., Zambaldi, V. F., Gruslys, A., Lazaridou, A., Tuyls, K., Pérolat, J., . . . Graepel, T. (2017). A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning.. In I. Guyon, U. V. Luxburg, S. Bengio, H. M. Wallach, R. Fergus, S. V. N. Vishwanathan, & R. Garnett (Eds.), NIPS (pp. 4190-4203). Retrieved from https://proceedings.neurips.cc/paper/2017
Lanctot, M., Zambaldi, V., Gruslys, A., Lazaridou, A., Tuyls, K., Perolat, J., . . . Graepel, T. (2017). A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning. The Thirty-first Annual Conference on Neural Information Processing Systems (NIPS). Retrieved from https://papers.nips.cc/
Perolat, J., Leibo, J. Z., Zambaldi, V., Beattie, C., Tuyls, K., & Graepel, T. (2017). A multi-agent reinforcement learning model of common-pool resource appropriation. The Thirty-first Annual Conference on Neural Information Processing Systems (NIPS). Retrieved from https://papers.nips.cc/
Evolving coverage behaviours for MAVs using NEAT (Conference Paper)
Butterworth, J., Tuyls, K., Broecker, B., & Paoletti, P. (2017). Evolving coverage behaviours for MAVs using NEAT. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS Vol. 3 (pp. 1886-1888).
Palmer, G., Tuyls, K., Bloembergen, D., & Savani, R. (2018). Lenient Multi-Agent Deep Reinforcement Learning. In PROCEEDINGS OF THE 17TH INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS AND MULTIAGENT SYSTEMS (AAMAS' 18) (pp. 443-451). Retrieved from https://www.webofscience.com/
A multi-agent reinforcement learning model of common-pool resource appropriation. (Conference Paper)
Pérolat, J., Leibo, J. Z., Zambaldi, V. F., Beattie, C., Tuyls, K., & Graepel, T. (2017). A multi-agent reinforcement learning model of common-pool resource appropriation.. In I. Guyon, U. V. Luxburg, S. Bengio, H. M. Wallach, R. Fergus, S. V. N. Vishwanathan, & R. Garnett (Eds.), NIPS (pp. 3643-3652). Retrieved from https://proceedings.neurips.cc/paper/2017
Decentralised Online Planning for Multi-Robot Warehouse Commissioning (Conference Paper)
Claes, D., Oliehoek, F., Baier, H., & Tuyls, K. (2017). Decentralised Online Planning for Multi-Robot Warehouse Commissioning. In AAMAS'17: PROCEEDINGS OF THE 16TH INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS AND MULTIAGENT SYSTEMS (pp. 492-500). Retrieved from https://www.webofscience.com/
Collenette, J., Atkinson, K., Bloembergen, D., & Tuyls, K. (2017). Environmental effects on simulated emotional and moody agents. KNOWLEDGE ENGINEERING REVIEW, 32. doi:10.1017/S0269888917000170DOI: 10.1017/S0269888917000170
Mood Modelling within Reinforcement Learning (Conference Paper)
Collenette, J., Atkinson, K., Bloembergen, D., & Tuyls, K. (2017). Mood Modelling within Reinforcement Learning. In FOURTEENTH EUROPEAN CONFERENCE ON ARTIFICIAL LIFE (ECAL 2017) (pp. 106-113). Retrieved from https://www.webofscience.com/
2016
de Bruin, T., Kober, J., Tuyls, K., & Babushka, R. (2016). Improved Deep Reinforcement Learning for Robotics Through Distribution-based Experience Retention. In IROS 2016 - IEEE/RSJ International Conference on Intelligent Robots and Systems. Daejeon, Korea.
Ranjbar-Sahraei, B., Bou Ammar, H., Tuyls, K., & Weiss, G. (2016). On the prevalence of hierarchies in social networks. Social Network Analysis and Mining, 6(1). doi:10.1007/s13278-016-0363-8DOI: 10.1007/s13278-016-0363-8
Klima, R., Bloembergen, D., Savani, R., Tuyls, K., Hennes, D., & Izzo, D. (2016). Space Debris Removal: A Game Theoretic Analysis. Games, 7(3). doi:10.3390/g7030020DOI: 10.3390/g7030020
Jonker, C., Marsella, S., Thangarajah, J., & Tuyls, K. (2016). Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems. (2016 ed.). K. Tuyls (Ed.), ACM.
Entity resolution in disjoint graphs: An application on genealogical data (Journal article)
Rahmani, H., Ranjbar-Sahraei, B., Weiss, G., & Tuyls, K. (2016). Entity resolution in disjoint graphs: An application on genealogical data. INTELLIGENT DATA ANALYSIS, 20(2), 455-475. doi:10.3233/IDA-160814DOI: 10.3233/IDA-160814
A Telepresence-Robot Approach for Efficient Coordination of Swarms (Conference Paper)
Tuyls, K., Alers, S., Cucco, E., Claes, D., & Bloembergen, D. (2016). A Telepresence-Robot Approach for Efficient Coordination of Swarms. In ALIFE 2016, THE FIFTEENTH INTERNATIONAL CONFERENCE ON THE SYNTHESIS AND SIMULATION OF LIVING SYSTEMS (pp. 666-673). Retrieved from https://www.webofscience.com/
A telepresence-robot approach for efficient coordination of swarms (Conference Paper)
Tuyls, K., Alers, S., Cucco, E., Claes, D., & Bloembergen, D. (2016). A telepresence-robot approach for efficient coordination of swarms. In Proceedings of the Artificial Life Conference 2016, ALIFE 2016.
Bayesian Inference in Dynamic Domains using Logical OR Gates (Conference Paper)
Claessens, R., de Waal, A., de Villiers, P., Penders, A., Pavlin, G., & Tuyls, K. (2016). Bayesian Inference in Dynamic Domains using Logical OR Gates. In PROCEEDINGS OF THE 18TH INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS, VOL 2 (ICEIS) (pp. 134-142). doi:10.5220/0005768601340142DOI: 10.5220/0005768601340142
McGuire, K., Croon, G. D., Wagter, C. D., Tuyls, K., & Kappen, H. J. (2016). Efficient Optical flow and Stereo Vision for Velocity Estimation and Obstacle Avoidance on an Autonomous Pocket Drone.. CoRR, abs/1612.06702.
Introduction (Conference Paper)
Thangarajah, J., Tuyls, K., Jonker, C., & Marsella, S. (2016). Introduction. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS (pp. iii-iv).
McGuire, K., Croon, G. C. H. E. D., Wagter, C. D., Remes, B., Tuyls, K., & Kappen, H. J. (2016). Local histogram matching for efficient optical flow computation applied to velocity estimation on pocket drones.. In D. Kragic, A. Bicchi, & A. D. Luca (Eds.), ICRA (pp. 3255-3260). IEEE. Retrieved from https://ieeexplore.ieee.org/xpl/conhome/7478842/proceeding
Li, X., Zhang, C., Hao, J., Tuyls, K., Chen, S., & Feng, Z. (2016). Socially-Aware Multiagent Learning: Towards Socially Optimal Outcomes. In ECAI 2016: 22ND EUROPEAN CONFERENCE ON ARTIFICIAL INTELLIGENCE Vol. 285 (pp. 533-541). doi:10.3233/978-1-61499-672-9-533DOI: 10.3233/978-1-61499-672-9-533
Klima, R., Bloembergen, D., Savani, R., Tuyls, K., Hennes, D., & Izzo, D. (2016). Space Debris Removal: A Game Theoretic Analysis. In ECAI 2016: 22ND EUROPEAN CONFERENCE ON ARTIFICIAL INTELLIGENCE Vol. 285 (pp. 1658-1659). doi:10.3233/978-1-61499-672-9-1658DOI: 10.3233/978-1-61499-672-9-1658
TARTARUS: A Multi-Agent Platform for Bridging the Gap between Cyber and Physical Systems (Demonstration). (Conference Paper)
Semwal, T., Nikhil, S., Jha, S. S., & Nair, S. B. (2016). TARTARUS: A Multi-Agent Platform for Bridging the Gap between Cyber and Physical Systems (Demonstration).. In C. M. Jonker, S. Marsella, J. Thangarajah, & K. Tuyls (Eds.), AAMAS (pp. 1493-1495). ACM. Retrieved from http://dl.acm.org/citation.cfm?id=2936924
Collenette, J., Atkinson, K., Bloembergen, D., & Tuyls, K. (2016). The Effect of Mobility and Emotion on Interactions in Multi-Agent Systems. In PROCEEDINGS OF THE EIGHTH EUROPEAN STARTING AI RESEARCHER SYMPOSIUM (STAIRS 2016) Vol. 284 (pp. 39-50). doi:10.3233/978-1-61499-682-8-39DOI: 10.3233/978-1-61499-682-8-39
Chen, S., Zhou, S., Weiss, G., & Tuyls, K. (2016). Using Transfer Learning to Model Unknown Opponents in Automated Negotiations. In Unknown Conference (pp. 175-192). Springer International Publishing. doi:10.1007/978-3-319-30307-9_11DOI: 10.1007/978-3-319-30307-9_11
2015
2D-SDF-SLAM: A Signed Distance Function based SLAM Frontend for Laser Scanners (Conference Paper)
Fossel, J. -D., Tuyls, K., & Sturm, J. (2015). 2D-SDF-SLAM: A Signed Distance Function based SLAM Frontend for Laser Scanners. In 2015 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS) (pp. 1949-1955). Retrieved from https://www.webofscience.com/
Mocanu, D., Ammar, H. B., Lowet, D., Driessens, K., Liotta, A., Weiss, G., & Tuyls, K. (2015). Factored four way conditional restricted Boltzmann machines for activity recognition. Pattern Recognition Letters, 66, 100-108. doi:10.1016/j.patrec.2015.01.013DOI: 10.1016/j.patrec.2015.01.013
Metastrategies in Large-Scale Bargaining Settings (Journal article)
Hennes, D., De Jong, S., Tuyls, K., & Gal, Y. K. (2015). Metastrategies in Large-Scale Bargaining Settings. ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY, 7(1). doi:10.1145/2774224DOI: 10.1145/2774224
Ranjbar-Sahraei, B., Ammar, H. B., Tuyls, K., & Weiss, G. (2015). On the Skewed Degree Distribution of Hierarchical Networks. In PROCEEDINGS OF THE 2015 IEEE/ACM INTERNATIONAL CONFERENCE ON ADVANCES IN SOCIAL NETWORKS ANALYSIS AND MINING (ASONAM 2015) (pp. 298-301). doi:10.1145/2808797.2809409DOI: 10.1145/2808797.2809409
Bloembergen, D., Tuyls, K., Hennes, D., & Kaisers, M. (2015). Evolutionary Dynamics of Multi-Agent Learning: A Survey. JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH, 53, 659-697. doi:10.1613/jair.4818DOI: 10.1613/jair.4818
On the Skewed Degree Distribution of Hierarchical Networks (Conference Paper)
Ranjbar, B., Bou-Ammar, H., Tuyls, K., & Weiss, G. (2015). On the Skewed Degree Distribution of Hierarchical Networks. In IEEE/ACM International Conference on Advances in Social Analysis and Mining (pp. 298-301). Paris, France.
Bio-inspired multi-robot systems (Chapter)
Ranjbar-Sahraei, B., Tuyls, K., Caliskanelli, I., Broeker, B., Claes, D., Alers, S., & Weiss, G. (2015). Bio-inspired multi-robot systems. In Biomimetic Technologies (pp. 273-299). Elsevier. doi:10.1016/b978-0-08-100249-0.00013-6DOI: 10.1016/b978-0-08-100249-0.00013-6
Trading in markets with noisy information: an evolutionary analysis (Journal article)
Bloembergen, D., Hennes, D., McBurney, P., & Tuyls, K. (2015). Trading in markets with noisy information: an evolutionary analysis. CONNECTION SCIENCE, 27(3), 253-268. doi:10.1080/09540091.2015.1039492DOI: 10.1080/09540091.2015.1039492
Effective Approximations for Multi-Robot Coordination in Spatially Distributed Tasks (Journal article)
Claes, D., Robbel, P., Oliehoek, F., Tuyls, K., Hennes, D., & Van Der Hoek, W. (2015). Effective Approximations for Multi-Robot Coordination in Spatially Distributed Tasks. Proceedings of the 14th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2015), 881-890. Retrieved from http://www.aamas2015.com/en/AAMAS_2015_USB/aamas/p881.pdf
Effective Approximations for Multi-Robot Coordination in Spatially Distributed Tasks (Conference Paper)
Claes, D., Robbel, P., Oliehoek, F. A., Tuyls, K., Hennes, D., & van der Hoek, W. (2015). Effective Approximations for Multi-Robot Coordination in Spatially Distributed Tasks. In PROCEEDINGS OF THE 2015 INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS & MULTIAGENT SYSTEMS (AAMAS'15) (pp. 881-890). Retrieved from https://www.webofscience.com/
HiDER: Query-Driven Entity Resolution for Historical Data (Conference Paper)
Ranjbar-Sahraei, B., Efremova, J., Rahmani, H., Calders, T., Tuyls, K., & Weiss, G. (2015). HiDER: Query-Driven Entity Resolution for Historical Data. In MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, PT III Vol. 9286 (pp. 281-284). doi:10.1007/978-3-319-23461-8_30DOI: 10.1007/978-3-319-23461-8_30
Human Robot-Team Interaction Towards the Factory of the Future (Conference Paper)
Claes, D., & Tuyls, K. (2015). Human Robot-Team Interaction Towards the Factory of the Future. In ARTIFICIAL LIFE AND INTELLIGENT AGENTS, ALIA 2014 Vol. 519 (pp. 61-72). doi:10.1007/978-3-319-18084-7_5DOI: 10.1007/978-3-319-18084-7_5
Hybrid Insect-Inspired Multi-Robot Coverage in Complex Environments (Conference Paper)
Broecker, B., Caliskanelli, I., Tuyls, K., Sklar, E. I., & Hennes, D. (2015). Hybrid Insect-Inspired Multi-Robot Coverage in Complex Environments. In TOWARDS AUTONOMOUS ROBOTIC SYSTEMS (TAROS 2015) Vol. 9287 (pp. 56-68). doi:10.1007/978-3-319-22416-9_8DOI: 10.1007/978-3-319-22416-9_8
Bloembergen, D., Caliskanelli, I., & Tuyls, K. (2015). Learning in Networked Interactions: A Replicator Dynamics Approach. ARTIFICIAL LIFE AND INTELLIGENT AGENTS, ALIA 2014, 519, 44-58. doi:10.1007/978-3-319-18084-7_4DOI: 10.1007/978-3-319-18084-7_4
Multi-Agent Target Tracking using Particle Filters enhanced with Context Data (Poster)
Claessens, R., de Waal, A., de Villiers, P., Penders, A., Pavlin, G., & Tuyls, K. (2015). Multi-Agent Target Tracking using Particle Filters enhanced with Context Data. Poster session presented at the meeting of Unknown Conference. Retrieved from https://www.webofscience.com/
Multi-Robot Coverage: A Bee Pheromone Signalling Approach (Conference Paper)
Caliskanelli, I., Broecker, B., & Tuyls, K. (2015). Multi-Robot Coverage: A Bee Pheromone Signalling Approach. In ARTIFICIAL LIFE AND INTELLIGENT AGENTS, ALIA 2014 Vol. 519 (pp. 124-140). doi:10.1007/978-3-319-18084-7_10DOI: 10.1007/978-3-319-18084-7_10
Efremova, J., Ranjbar-Sahraei, B., Rahmani, H., Oliehoek, F. A., Calders, T., Tuyls, K., & Weiss, G. (2015). Multi-Source Entity Resolution for Genealogical Data. In Population Reconstruction (pp. 129-154). Springer International Publishing. doi:10.1007/978-3-319-19884-2_7DOI: 10.1007/978-3-319-19884-2_7
Preface (Book)
Dixon, C., & Tuyls, K. (2015). Preface (Vol. 9287).
Proceedings of Towards Autonomous Robotic Systems - 16th Annual Conference (Book)
Dixon, C., & Tuyls, K. (Eds.) (2015). Proceedings of Towards Autonomous Robotic Systems - 16th Annual Conference (Vol. 9287). Springer.
Social Insect-Inspired Multi-Robot Coverage (Conference Paper)
Broecker, B., Caliskanelli, I., Tuyls, K., Sklar, E., & Hennes, D. (2015). Social Insect-Inspired Multi-Robot Coverage. In PROCEEDINGS OF THE 2015 INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS & MULTIAGENT SYSTEMS (AAMAS'15) (pp. 1775-1776). Retrieved from https://www.webofscience.com/
Survival of the Chartist: An Evolutionary Agent-Based Analysis of Stock Market Trading (Conference Paper)
Bloembergen, D., Hennes, D., Parsons, S., & Tuyls, K. (2015). Survival of the Chartist: An Evolutionary Agent-Based Analysis of Stock Market Trading. In PROCEEDINGS OF THE 2015 INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS & MULTIAGENT SYSTEMS (AAMAS'15) (pp. 1699-1700). Retrieved from https://www.webofscience.com/
Towards Autonomous Robotic Systems (Conference Paper)
Dixon, C., & Tuyls, K. (Eds.) (2015). Towards Autonomous Robotic Systems. In . Springer International Publishing. doi:10.1007/978-3-319-22416-9DOI: 10.1007/978-3-319-22416-9
Winning the RoboCup@Work 2014 Competition: The smARTLab Approach (Chapter)
Broecker, B., Claes, D., Fossel, J., & Tuyls, K. (2015). Winning the RoboCup@Work 2014 Competition: The smARTLab Approach. In Unknown Book (Vol. 8992, pp. 142-154). doi:10.1007/978-3-319-18615-3_12DOI: 10.1007/978-3-319-18615-3_12
2014
Automated Transfer for Reinforcement Learning Tasks (Journal article)
Bou Ammar, H., Chen, S., Tuyls, K., & Weiss, G. (2014). Automated Transfer for Reinforcement Learning Tasks. KI - Künstliche Intelligenz, 28(1), 7-14. doi:10.1007/s13218-013-0286-8DOI: 10.1007/s13218-013-0286-8
Transfer for Automated Negotiation (Journal article)
Chen, S., Ammar, H. B., Tuyls, K., & Weiss, G. (2014). Transfer for Automated Negotiation. KI - Künstliche Intelligenz, 28(1), 21-27. doi:10.1007/s13218-013-0284-xDOI: 10.1007/s13218-013-0284-x
Jong, S. D., Uyttendaele, S., & Tuyls, K. (2014). Learning to Reach Agreement in a Continuous Ultimatum Game. Journal Of Artificial Intelligence Research, Volume 33, pages 551-574, 2008. Retrieved from http://dx.doi.org/10.1613/jair.2685
A decentralized approach for convention emergence in multi-agent systems (Journal article)
Mihaylov, M., Tuyls, K., & Nowe, A. (2014). A decentralized approach for convention emergence in multi-agent systems. AUTONOMOUS AGENTS AND MULTI-AGENT SYSTEMS, 28(5), 749-778. doi:10.1007/s10458-013-9240-2DOI: 10.1007/s10458-013-9240-2
An automated measure of MDP similarity for transfer in reinforcement learning (Conference Paper)
Ammar, H. B., Eaton, E., Taylor, M. E., Mocanu, D. C., Driessens, K., Weiss, G., & Tüyls, K. (2014). An automated measure of MDP similarity for transfer in reinforcement learning. In AAAI Workshop - Technical Report Vol. WS-14-07 (pp. 31-37).
Applied Robotics: Precision Placement in RoboCup@Work (Conference Paper)
Alers, S., Claes, D., Fossel, J., Hennes, D., & Tuyls, K. (2014). Applied Robotics: Precision Placement in RoboCup@Work. In AAMAS'14: PROCEEDINGS OF THE 2014 INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS & MULTIAGENT SYSTEMS (pp. 1681-1682). Retrieved from https://www.webofscience.com/
Biologically Inspired Multi-Robot Foraging (Conference Paper)
Alers, S., Claes, D., Tuyls, K., & Weiss, G. (2014). Biologically Inspired Multi-Robot Foraging. In AAMAS'14: PROCEEDINGS OF THE 2014 INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS & MULTIAGENT SYSTEMS (pp. 1683-1684). Retrieved from https://www.webofscience.com/
Contextual entity resolution approach for genealogical data (Conference Paper)
Rahmani, H., Ranjbar-Sahraei, B., Weiss, G., & Tuyls, K. (2014). Contextual entity resolution approach for genealogical data. In CEUR Workshop Proceedings Vol. 1226 (pp. 168-179).
Effects of Evolution on the Emergence of Scale Free Networks (Conference Paper)
Ranjbar-Sahraei, B., Bloembergen, D., Ammar, H. B., Tuyls, K., & Weiss, G. (2014). Effects of Evolution on the Emergence of Scale Free Networks. In ALIFE 2014: THE FOURTEENTH INTERNATIONAL CONFERENCE ON THE SYNTHESIS AND SIMULATION OF LIVING SYSTEMS (pp. 376-383). doi:10.7551/978-0-262-32621-6-ch060DOI: 10.7551/978-0-262-32621-6-ch060
Evolution of Cooperation in Arbitrary Complex Networks (Conference Paper)
Ranjbar-Sahraei, B., Ammar, H. B., Bloembergen, D., Tuyls, K., & Weiss, G. (2014). Evolution of Cooperation in Arbitrary Complex Networks. In AAMAS'14: PROCEEDINGS OF THE 2014 INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS & MULTIAGENT SYSTEMS (pp. 677-684). Retrieved from https://www.webofscience.com/
How to Win RoboCup@Work? (Conference Paper)
Alers, S., Claes, D., Fossel, J., Hennes, D., Tuyls, K., & Weiss, G. (2014). How to Win RoboCup@Work?. In ROBOCUP 2013: ROBOT WORLD CUP XVII Vol. 8371 (pp. 147-158). doi:10.1007/978-3-662-44468-9_14DOI: 10.1007/978-3-662-44468-9_14
Influencing Social Networks: An Optimal Control Study (Conference Paper)
Bloembergen, D., Ranjbar-Sahraei, B., Ammar, H. B., Tuyls, K., & Weiss, G. (2014). Influencing Social Networks: An Optimal Control Study. In 21ST EUROPEAN CONFERENCE ON ARTIFICIAL INTELLIGENCE (ECAI 2014) Vol. 263 (pp. 105-+). doi:10.3233/978-1-61499-419-0-105DOI: 10.3233/978-1-61499-419-0-105
Insect-Inspired Robot Coordination: Foraging and Coverage (Conference Paper)
Alers, S., Tuyls, K., Ranjbar-Sahraei, B., Claes, D., & Weiss, G. (2014). Insect-Inspired Robot Coordination: Foraging and Coverage. In ALIFE 2014: THE FOURTEENTH INTERNATIONAL CONFERENCE ON THE SYNTHESIS AND SIMULATION OF LIVING SYSTEMS (pp. 761-768). doi:10.7551/978-0-262-32621-6-ch123DOI: 10.7551/978-0-262-32621-6-ch123
Robustness Analysis of Negotiation Strategies through Multiagent Learning in Repeated Negotiation Games (Conference Paper)
Hao, J., Chen, S., Weiss, G., Leung, H. -F., & Tuyls, K. (2014). Robustness Analysis of Negotiation Strategies through Multiagent Learning in Repeated Negotiation Games. In Unknown Conference (pp. 41-56). Springer International Publishing. doi:10.1007/978-3-319-11584-9_4DOI: 10.1007/978-3-319-11584-9_4
Spatial evolutionary game-theoretic perspective on agent-based complex negotiations (Conference Paper)
Chen, S., Hao, J., Weiss, G., Tuyls, K., & Leung, H. -F. (2014). Spatial evolutionary game-theoretic perspective on agent-based complex negotiations. In 21ST EUROPEAN CONFERENCE ON ARTIFICIAL INTELLIGENCE (ECAI 2014) Vol. 263 (pp. 983-+). doi:10.3233/978-1-61499-419-0-983DOI: 10.3233/978-1-61499-419-0-983
Theory of Cooperation in Complex Social Networks (Conference Paper)
Ranjbar-Sahraei, B., Ammar, H. B., Bloembergen, D., Tuyls, K., & Weiss, G. (2014). Theory of Cooperation in Complex Social Networks. In PROCEEDINGS OF THE TWENTY-EIGHTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE (pp. 1471-1477). Retrieved from https://www.webofscience.com/
Trading in markets with noisy information: An evolutionary analysis (Conference Paper)
Bloembergen, D., Hennes, D., McBurney, P., & Tuyls, K. (2014). Trading in markets with noisy information: An evolutionary analysis. In AAMAS 2014 Workshop on Adaptive and Learning Agents, ALA 2014.
Valuation of cooperation and defection in small-world networks: A behavioral robotic approach (Conference Paper)
Ranjbar-Sahraei, B., Groothuis, I. M., Tuyls, K., & Weiss, G. (2014). Valuation of cooperation and defection in small-world networks: A behavioral robotic approach. In Belgian/Netherlands Artificial Intelligence Conference (pp. 103-110).
2013
Conditional restricted Boltzmann machines for negotiations in highly competitive and complex domains (Conference Paper)
Chen, S., Bou Ammar, H., Tuyls, K., & Weiss, G. (2013). Conditional restricted Boltzmann machines for negotiations in highly competitive and complex domains. In IJCAI International Joint Conference on Artificial Intelligence (pp. 69-75).
Automatically Mapped Transfer between Reinforcement Learning Tasks via Three-Way Restricted Boltzmann Machines (Conference Paper)
Ammar, H. B., Mocanu, D. C., Taylor, M. E., Driessens, K., Tuyls, K., & Weiss, G. (2013). Automatically Mapped Transfer between Reinforcement Learning Tasks via Three-Way Restricted Boltzmann Machines. In Unknown Conference (pp. 449-464). Springer Berlin Heidelberg. doi:10.1007/978-3-642-40991-2_29DOI: 10.1007/978-3-642-40991-2_29
Telepresence robots as a research platform for AI (Conference Paper)
Alers, S., Bloembergen, D., Claes, D., Fossel, J., Hennes, D., & Tuyls, K. (2013). Telepresence robots as a research platform for AI. In AAAI Spring Symposium - Technical Report Vol. SS-13-04 (pp. 2-3).
OctoSLAM: A 3D mapping approach to situational awareness of unmanned aerial vehicles (Conference Paper)
Fossel, J., Hennes, D., Claes, D., Alers, S., & Tuyls, K. (2013). OctoSLAM: A 3D mapping approach to situational awareness of unmanned aerial vehicles. In 2013 International Conference on Unmanned Aircraft Systems (ICUAS). IEEE. doi:10.1109/icuas.2013.6564688DOI: 10.1109/icuas.2013.6564688
Swarm-based evaluation of nonparametric SysML mechatronics system design (Conference Paper)
Chami, M., Ammar, H. B., Voos, H., Tuyls, K., & Weiss, G. (2013). Swarm-based evaluation of nonparametric SysML mechatronics system design. In 2013 IEEE International Conference on Mechatronics (ICM). IEEE. doi:10.1109/icmech.2013.6518576DOI: 10.1109/icmech.2013.6518576
A macroscopic model for multi-robot stigmergic coverage (Conference Paper)
Ranjbar-Sahraei, B., Weiss, G., & Tuyls, K. (2013). A macroscopic model for multi-robot stigmergic coverage. In 12th International Conference on Autonomous Agents and Multiagent Systems 2013, AAMAS 2013 Vol. 2 (pp. 1233-1234).
An Interactive, web-based tool for genealogical entity resolution (Conference Paper)
Efremova, J., Ranjbar-Sahraei, B., Oliehoek, F. A., Calders, T., & Tuyls, K. (2013). An Interactive, web-based tool for genealogical entity resolution. In Belgian/Netherlands Artificial Intelligence Conference (pp. 376-377).
Applied robotics: Precision placement in RoboCup@Work (Conference Paper)
Alers, S., Claes, D., Fossel, J., Hennes, D., & Tuyls, K. (2013). Applied robotics: Precision placement in RoboCup@Work. In Belgian/Netherlands Artificial Intelligence Conference (pp. 370-371).
Automated negotiation based on sparse pseudo-input Gaussian processes (Conference Paper)
Chen, S., Ammar, H. B., Tuyls, K., & Weiss, G. (2013). Automated negotiation based on sparse pseudo-input Gaussian processes. In Belgian/Netherlands Artificial Intelligence Conference (pp. 307-308).
Automatic transfer between negotiation tasks (Conference Paper)
Chen, S., Ammar, H. B., Driessens, K., Tuyls, K., & Weiss, G. (2013). Automatic transfer between negotiation tasks. In AAMAS 2013 Workshop on Adaptive and Learning Agents, ALA 2013.
Development of an Autonomous RC-car (Conference Paper)
Claes, D., Fossel, J., Broecker, B., Hennes, D., & Tuyls, K. (2013). Development of an Autonomous RC-car. In Unknown Conference (pp. 108-120). Springer Berlin Heidelberg. doi:10.1007/978-3-642-40849-6_10DOI: 10.1007/978-3-642-40849-6_10
Effective approximations for planning with spatially distributed tasks (Conference Paper)
Claes, D., Robbel, P., Oliehoek, F. A., Hennes, D., & Tuyls, K. (2013). Effective approximations for planning with spatially distributed tasks. In Belgian/Netherlands Artificial Intelligence Conference (pp. 33-40).
OctoSLAM: A 3D mapping approach to situational awareness of unmanned aerial vehicles (Conference Paper)
Fossel, J., Hennes, D., Alers, S., Claes, D., & Tuyls, K. (2013). OctoSLAM: A 3D mapping approach to situational awareness of unmanned aerial vehicles. In 12th International Conference on Autonomous Agents and Multiagent Systems 2013, AAMAS 2013 Vol. 2 (pp. 1363-1364).
Optimizing complex automated negotiation using sparse pseudo-input Gaussian processes (Conference Paper)
Chen, S., Ammar, H. B., Tuyls, K., & Weiss, G. (2013). Optimizing complex automated negotiation using sparse pseudo-input Gaussian processes. In 12th International Conference on Autonomous Agents and Multiagent Systems 2013, AAMAS 2013 Vol. 1 (pp. 707-714).
Reinforcement Learning for Self-organizing Wake-Up Scheduling in Wireless Sensor Networks (Conference Paper)
Mihaylov, M., Le Borgne, Y. -A., Tuyls, K., & Nowé, A. (2013). Reinforcement Learning for Self-organizing Wake-Up Scheduling in Wireless Sensor Networks. In Unknown Conference (pp. 382-396). Springer Berlin Heidelberg. doi:10.1007/978-3-642-29966-7_25DOI: 10.1007/978-3-642-29966-7_25
StiCo in action (Conference Paper)
Ranjbar-Sahraei, B., Alers, S., Tuyls, K., & Weiss, G. (2013). StiCo in action. In 12th International Conference on Autonomous Agents and Multiagent Systems 2013, AAMAS 2013 Vol. 2 (pp. 1403-1404).
Toward soft heterogeneity in robotic swarms (Conference Paper)
Ranjbar-Sahraei, B., Alers, S., Staňková, K., Tuyls, K., & Weiss, G. (2013). Toward soft heterogeneity in robotic swarms. In Belgian/Netherlands Artificial Intelligence Conference (pp. 384-385).
2012
A nonparametric evaluation of sysML-based mechatronic conceptual design (Conference Paper)
Chami, M., Ammar, H. B., Voos, H., Tuyls, K., & Weiss, G. (2012). A nonparametric evaluation of sysML-based mechatronic conceptual design. In Belgian/Netherlands Artificial Intelligence Conference.
COCALU: Convex outline collision avoidance under localization uncertainty [Demonstration] (Conference Paper)
Claes, D., Hennes, D., & Tuyls, K. (2012). COCALU: Convex outline collision avoidance under localization uncertainty [Demonstration]. In Belgian/Netherlands Artificial Intelligence Conference.
Collision avoidance under bounded localization uncertainty (Conference Paper)
Claes, D., Hennes, D., Tuyls, K., & Meeussen, W. (2012). Collision avoidance under bounded localization uncertainty. In 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE. doi:10.1109/iros.2012.6386125DOI: 10.1109/iros.2012.6386125
Reinforcement learning transfer via sparse coding (Conference Paper)
Ammar, H. B., Tuyls, K., Taylor, M. E., Driessens, K., & Weiss, G. (2012). Reinforcement learning transfer via sparse coding. In Belgian/Netherlands Artificial Intelligence Conference.
STIGMERGIC LANDMARK OPTIMIZATION (Journal article)
LEMMENS, N., & TUYLS, K. (2012). STIGMERGIC LANDMARK OPTIMIZATION. Advances in Complex Systems, 15(08), 1150025. doi:10.1142/s0219525911500251DOI: 10.1142/s0219525911500251
Transfer learning for bilateral multi-issue negotiation (Conference Paper)
Chen, S., Ammar, H. B., Tuyls, K., & Weiss, G. (2012). Transfer learning for bilateral multi-issue negotiation. In Belgian/Netherlands Artificial Intelligence Conference.
Preface (Book)
Cossentino, M., Kaisers, M., Tuyls, K., & Weiss, G. (2012). Preface (Vol. 7541 LNAI).
Evolutionary Dynamics of Ant Colony Optimization (Conference Paper)
Bou Ammar, H., Tuyls, K., & Kaisers, M. (2012). Evolutionary Dynamics of Ant Colony Optimization. In Unknown Conference (pp. 40-52). Springer Berlin Heidelberg. doi:10.1007/978-3-642-33690-4_6DOI: 10.1007/978-3-642-33690-4_6
Using Time as a Strategic Element in Continuous Double Auctions (Conference Paper)
Neumann, M., Tuyls, K., & Kaisers, M. (2012). Using Time as a Strategic Element in Continuous Double Auctions. In Unknown Conference (pp. 106-115). Springer Berlin Heidelberg. doi:10.1007/978-3-642-33690-4_11DOI: 10.1007/978-3-642-33690-4_11
Evolutionary advantage of foresight in markets (Conference Paper)
Hennes, D., Bloembergen, D., Kaisers, M., Tuyls, K., & Parsons, S. (2012). Evolutionary advantage of foresight in markets. In Proceedings of the 14th annual conference on Genetic and evolutionary computation. ACM. doi:10.1145/2330163.2330294DOI: 10.1145/2330163.2330294
Decentralised reinforcement learning for energy-efficient scheduling in wireless sensor networks (Journal article)
Mihaylov, M., Borgne, Y. A. L., Tuyls, K., & Nowé, A. (2012). Decentralised reinforcement learning for energy-efficient scheduling in wireless sensor networks. International Journal of Communication Networks and Distributed Systems, 9(3/4), 207. doi:10.1504/ijcnds.2012.048871DOI: 10.1504/ijcnds.2012.048871
Multi-agent Learning and the Reinforcement Gradient (Conference Paper)
Kaisers, M., Bloembergen, D., & Tuyls, K. (2012). Multi-agent Learning and the Reinforcement Gradient. In Unknown Conference (pp. 145-159). Springer Berlin Heidelberg. doi:10.1007/978-3-642-34799-3_10DOI: 10.1007/978-3-642-34799-3_10
Multi-robot collision avoidance with localization uncertainty (Conference Paper)
Hennes, D., Claes, D., Meeussen, W., & Tuyls, K. (2012). Multi-robot collision avoidance with localization uncertainty. In 11th International Conference on Autonomous Agents and Multiagent Systems 2012, AAMAS 2012: Innovative Applications Track Vol. 2 (pp. 672-679).
Multiagent Learning: Basics, Challenges, and Prospects (Conference Paper)
Tuyls, K., & Weiss, G. (2012). Multiagent Learning: Basics, Challenges, and Prospects. In AI Magazine Vol. 33 (pp. 41-52). Wiley. doi:10.1609/aimag.v33i3.2426DOI: 10.1609/aimag.v33i3.2426
Preface for the special issue on Games and AI (Journal article)
Winands, M. H. M., Björnsson, Y., & Tuyls, K. (2012). Preface for the special issue on Games and AI. Entertainment Computing, 3(3), 49-50. doi:10.1016/j.entcom.2012.07.001DOI: 10.1016/j.entcom.2012.07.001
Reinforcement Learning Transfer Using a Sparse Coded Inter-task Mapping (Conference Paper)
Ammar, H. B., Taylor, M. E., Tuyls, K., & Weiss, G. (2012). Reinforcement Learning Transfer Using a Sparse Coded Inter-task Mapping. In Unknown Conference (pp. 1-16). Springer Berlin Heidelberg. doi:10.1007/978-3-642-34799-3_1DOI: 10.1007/978-3-642-34799-3_1
Reinforcement learning transfer via sparse coding (Conference Paper)
Ammar, H. B., Tuyls, K., Taylor, M. E., Driessens, K., & Weiss, G. (2012). Reinforcement learning transfer via sparse coding. In 11th International Conference on Autonomous Agents and Multiagent Systems 2012, AAMAS 2012: Innovative Applications Track Vol. 1 (pp. 89-96).
2011
Augmented mobile telepresence with assisted control (Conference Paper)
Alers, S., Bloembergen, D., Hennes, D., & Tuyls, K. (2011). Augmented mobile telepresence with assisted control. In Belgian/Netherlands Artificial Intelligence Conference.
Bee-inspired foraging in a real-life autonomous robot collective (Conference Paper)
Lemmens, N., Alers, S., & Tuyls, K. (2011). Bee-inspired foraging in a real-life autonomous robot collective. In Belgian/Netherlands Artificial Intelligence Conference.
Common sub-space transfer for reinforcement learning tasks (Conference Paper)
Ammar, H. B., Taylor, M. E., Tuyls, K., & Weiss, G. (2011). Common sub-space transfer for reinforcement learning tasks. In Belgian/Netherlands Artificial Intelligence Conference.
DESYDE: Decentralized (De)synchronization in Wireless Sensor Networks (Conference Paper)
Mihaylov, M., Le Borgne, Y. A., Tuyls, K., & Noẃe, A. (2011). DESYDE: Decentralized (De)synchronization in Wireless Sensor Networks. In Belgian/Netherlands Artificial Intelligence Conference.
Lenient learning in a multiplayer Stag Hunt (Conference Paper)
Bloembergen, D., de Jong, S., & Tuyls, K. (2011). Lenient learning in a multiplayer Stag Hunt. In Belgian/Netherlands Artificial Intelligence Conference.
Meta-strategies in the Colored Trails Game (Conference Paper)
de Jong, S., Hennes, D., Tuyls, K., & Gal, Y. (2011). Meta-strategies in the Colored Trails Game. In Belgian/Netherlands Artificial Intelligence Conference.
Multi-Agent based simulation of FOREX exchange market (Conference Paper)
Delage, V., Brandlhuber, C., Tuyls, K., & Weiss, G. (2011). Multi-Agent based simulation of FOREX exchange market. In Belgian/Netherlands Artificial Intelligence Conference.
Opponent Modeling with pomdps (Conference Paper)
Mescheder, D., Tuyls, K., & Kaisers, M. (2011). Opponent Modeling with pomdps. In Belgian/Netherlands Artificial Intelligence Conference.
FAQ-learning in matrix games: Demonstrating convergence near Nash equilibria, and bifurcation of attractors in the Battle of Sexes (Conference Paper)
Kaisers, M., & Tuyls, K. (2011). FAQ-learning in matrix games: Demonstrating convergence near Nash equilibria, and bifurcation of attractors in the Battle of Sexes. In AAAI Workshop - Technical Report Vol. WS-11-13 (pp. 36-42).
Self-organizing synchronicity and desynchronicity using reinforcement learning (Conference Paper)
Mihaylov, M., Le Borgne, Y. A., Nowé, A., & Tuyls, K. (2011). Self-organizing synchronicity and desynchronicity using reinforcement learning. In ICAART 2011 - Proceedings of the 3rd International Conference on Agents and Artificial Intelligence Vol. 2 (pp. 94-103).
Bee-inspired foraging in an embodied swarm (Conference Paper)
Alers, S., Bloembergen, D., Hennes, D., De Jong, S., Kaisers, M., Lemmens, N., . . . Weiss, G. (2011). Bee-inspired foraging in an embodied swarm. In 10th International Conference on Autonomous Agents and Multiagent Systems 2011, AAMAS 2011 Vol. 2 (pp. 1237-1238).
Distributed cooperation in wireless sensor networks (Conference Paper)
Mihaylov, M., Le Borgne, Y. A., Nowe, A., & Tuyls, K. (2011). Distributed cooperation in wireless sensor networks. In 10th International Conference on Autonomous Agents and Multiagent Systems 2011, AAMAS 2011 Vol. 1 (pp. 233-240).
Empirical and theoretical support for lenient learning (Conference Paper)
Bloembergen, D., Kaisers, M., & Tuyls, K. (2011). Empirical and theoretical support for lenient learning. In 10th International Conference on Autonomous Agents and Multiagent Systems 2011, AAMAS 2011 Vol. 2 (pp. 1039-1040).
Human-inspired computational fairness (Journal article)
de Jong, S., & Tuyls, K. (2011). Human-inspired computational fairness. Autonomous Agents and Multi-Agent Systems, 22(1), 103-126. doi:10.1007/s10458-010-9122-9DOI: 10.1007/s10458-010-9122-9
Metastrategies in the colored trails game (Conference Paper)
De Jong, S., Hennes, D., Tuyls, K., & Gal, Y. (2011). Metastrategies in the colored trails game. In 10th International Conference on Autonomous Agents and Multiagent Systems 2011, AAMAS 2011 Vol. 1 (pp. 513-520).
2010
A comparative study of multi-agent reinforcement learning dynamics (Conference Paper)
Bloembergen, D., Kaisers, M., & Tuyls, K. (2010). A comparative study of multi-agent reinforcement learning dynamics. In Belgian/Netherlands Artificial Intelligence Conference.
Lenient frequency adjusted Q-learning (Conference Paper)
Bloembergen, D., Kaisers, M., & Tuyls, K. (2010). Lenient frequency adjusted Q-learning. In Belgian/Netherlands Artificial Intelligence Conference.
RESQ-learning in stochastic games (Conference Paper)
Hennes, D., Kaisers, M., & Tuyls, K. (2010). RESQ-learning in stochastic games. In Proceedings of the Adaptive and Learning Agents Workshop, ALA 2010 - In Conjunction with the 9th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2010 (pp. 8-15).
Stigmergic landmark routing (Conference Paper)
Lemmens, N., & Tuyls, K. (2010). Stigmergic landmark routing. In Proceedings of the 12th annual conference on Genetic and evolutionary computation. ACM. doi:10.1145/1830483.1830491DOI: 10.1145/1830483.1830491
Abstraction and Generalization in Reinforcement Learning: A Summary and Framework (Conference Paper)
Ponsen, M., Taylor, M. E., & Tuyls, K. (2010). Abstraction and Generalization in Reinforcement Learning: A Summary and Framework. In Unknown Conference (pp. 1-32). Springer Berlin Heidelberg. doi:10.1007/978-3-642-11814-2_1DOI: 10.1007/978-3-642-11814-2_1
Adaptive and Learning Agents: Preface (Book)
Taylor, M. E., & Tuyls, K. (2010). Adaptive and Learning Agents: Preface (Vol. 5924 LNAI).
Decentralized Learning in Wireless Sensor Networks (Conference Paper)
Mihaylov, M., Tuyls, K., & Nowé, A. (2010). Decentralized Learning in Wireless Sensor Networks. In Unknown Conference (pp. 60-73). Springer Berlin Heidelberg. doi:10.1007/978-3-642-11814-2_4DOI: 10.1007/978-3-642-11814-2_4
Replicator Dynamics for Multi-agent Learning: An Orthogonal Approach (Conference Paper)
Kaisers, M., & Tuyls, K. (2010). Replicator Dynamics for Multi-agent Learning: An Orthogonal Approach. In Unknown Conference (pp. 49-59). Springer Berlin Heidelberg. doi:10.1007/978-3-642-11814-2_3DOI: 10.1007/978-3-642-11814-2_3
Learning with Whom to Communicate Using Relational Reinforcement Learning (Journal article)
Ponsen, M., Croonenborghs, T., Tuyls, K., Ramon, J., Driessens, K., van den Herik, J., & Postma, E. (2010). Learning with Whom to Communicate Using Relational Reinforcement Learning. Unknown Journal, 45-63. doi:10.1007/978-3-642-11688-9_2DOI: 10.1007/978-3-642-11688-9_2
Frequency adjusted multi-agent Q-learning (Conference Paper)
Kaisers, M., & Tuyls, K. (2010). Frequency adjusted multi-agent Q-learning. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS Vol. 1 (pp. 309-315).
Reports of the AAAI 2010 Conference Workshops (Conference Paper)
Aha, D. W., Boddy, M., Bulitko, V., Garcez, A. S. D., Doshi, P., Edelkamp, S., . . . van der Meyden, R. (2010). Reports of the AAAI 2010 Conference Workshops. In AI Magazine Vol. 31 (pp. 95-108). Wiley. doi:10.1609/aimag.v31i4.2318DOI: 10.1609/aimag.v31i4.2318
2009
Decentralized learning in wireless sensor networks (Conference Paper)
Mihaylov, M., Tuyls, K., & Nowé, A. (2009). Decentralized learning in wireless sensor networks. In Belgian/Netherlands Artificial Intelligence Conference (pp. 345-346).
Developing Novel Extensions to Support Prototyping for Interactive Social Robots (Conference Paper)
Ten Bhömer, M., Bartneck, C., Hu, J., Ahn, R., Tuyls, K., Delbressine, F., & Feijs, L. (2009). Developing Novel Extensions to Support Prototyping for Interactive Social Robots. In Belgian/Netherlands Artificial Intelligence Conference (pp. 11-17).
An evolutionary game-theoretic analysis of poker strategies (Journal article)
Ponsen, M., Tuyls, K., Kaisers, M., & Ramon, J. (2009). An evolutionary game-theoretic analysis of poker strategies. Entertainment Computing, 1(1), 39-45. doi:10.1016/j.entcom.2009.09.002DOI: 10.1016/j.entcom.2009.09.002
An evolutionary model of multi-agent learning with a varying exploration rate (Conference Paper)
Kaisers, M., Tuyls, K., Parsons, S., & Thuijsman, F. (2009). An evolutionary model of multi-agent learning with a varying exploration rate. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS Vol. 2 (pp. 1286-1287).
Learning to cooperate in a continuous tragedy of the commons (Conference Paper)
De Jong, S., & Tuyls, K. (2009). Learning to cooperate in a continuous tragedy of the commons. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS Vol. 2 (pp. 1124-1125).
Learning with whom to communicate using relational reinforcement learning (Conference Paper)
Ponsen, M., Croonenborghs, T., Tuyls, K., Ramon, J., & Driessens, K. (2009). Learning with whom to communicate using relational reinforcement learning. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS Vol. 2 (pp. 1214-1215).
State-coupled replicator dynamics (Conference Paper)
Hennes, D., Tuyls, K., & Rauterberg, M. (2009). State-coupled replicator dynamics. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS Vol. 2 (pp. 878-885).
Stigmergic landmark foraging (Conference Paper)
Lemmens, N., & Tuyls, K. (2009). Stigmergic landmark foraging. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS Vol. 2 (pp. 838-845).
2008
Bayes-relational learning of opponent models from incomplete information in no-limit poker (Conference Paper)
Ponsen, M., Ramon, J., Croonenborghs, T., Driessens, K., & Tuyls, K. (2008). Bayes-relational learning of opponent models from incomplete information in no-limit poker. In Proceedings of the National Conference on Artificial Intelligence Vol. 3 (pp. 1485-1486).
Auction Analysis by Normal Form Game Approximation (Conference Paper)
Kaisers, M., Tuyls, K., Thuijsman, F., & Parsons, S. (2008). Auction Analysis by Normal Form Game Approximation. In 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology. IEEE. doi:10.1109/wiiat.2008.261DOI: 10.1109/wiiat.2008.261
Collective intelligentwireless sensor networks (Conference Paper)
Mihaylov, M., Nowé, A., & Tuyls, K. (2008). Collective intelligentwireless sensor networks. In Belgian/Netherlands Artificial Intelligence Conference (pp. 169-176).
Discovering the game in auctions (Conference Paper)
Kaisers, M., Tuyls, K., Thuijsman, F., & Parsons, S. (2008). Discovering the game in auctions. In Belgian/Netherlands Artificial Intelligence Conference (pp. 113-120).
Formalizing Multi-state Learning Dynamics (Conference Paper)
Hennes, D., Tuyls, K., & Rauterberg, M. (2008). Formalizing Multi-state Learning Dynamics. In 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology. IEEE. doi:10.1109/wiiat.2008.33DOI: 10.1109/wiiat.2008.33
Stigmergic landmarks lead the way (Conference Paper)
Lemmens, N., & Tuyls, K. (2008). Stigmergic landmarks lead the way. In Belgian/Netherlands Artificial Intelligence Conference (pp. 129-136).
The dynamics of human behaviour in poker (Conference Paper)
Ponsen, M., Tuyls, K., de Jong, S., Ramon, J., Croonenborghs, T., & Driessens, K. (2008). The dynamics of human behaviour in poker. In Belgian/Netherlands Artificial Intelligence Conference (pp. 225-232).
The influence of physical appearance on a fair share (Conference Paper)
De Jong, S., Van De Ven, R., & Tuyls, K. (2008). The influence of physical appearance on a fair share. In Belgian/Netherlands Artificial Intelligence Conference (pp. 105-112).
Bee Behaviour in Multi-agent Systems (Conference Paper)
Lemmens, N., de Jong, S., Tuyls, K., & Nowé, A. (2008). Bee Behaviour in Multi-agent Systems. In Unknown Conference (pp. 145-156). Springer Berlin Heidelberg. doi:10.1007/978-3-540-77949-0_11DOI: 10.1007/978-3-540-77949-0_11
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface (Book)
Tuyls, K., Nowé, A., Guessoum, Z., & Kudenko, D. (2008). Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface (Vol. 4865 LNAI).
Priority Awareness: Towards a Computational Model of Human Fairness for Multi-agent Systems (Conference Paper)
de Jong, S., Tuyls, K., Verbeeck, K., & Roos, N. (2008). Priority Awareness: Towards a Computational Model of Human Fairness for Multi-agent Systems. In Unknown Conference (pp. 117-128). Springer Berlin Heidelberg. doi:10.1007/978-3-540-77949-0_9DOI: 10.1007/978-3-540-77949-0_9
Entertainment Computing in the Orbit (Conference Paper)
Rauterberg, M., Neerincx, M., Tuyls, K., & Loon, J. V. (n.d.). Entertainment Computing in the Orbit. In Unknown Conference (pp. 59-70). Springer US. doi:10.1007/978-0-387-09701-5_6DOI: 10.1007/978-0-387-09701-5_6
Fairness in multi-agent systems (Journal article)
JONG, S. D., TUYLS, K., & VERBEECK, K. (2008). Fairness in multi-agent systems. The Knowledge Engineering Review, 23(2), 153-180. doi:10.1017/s026988890800132xDOI: 10.1017/s026988890800132x
Kuijpers, B., Lemmens, V., Moelans, B., & Tuyls, K. (2008). Privacy Preserving ID3 over Horizontally, Vertically and Grid Partitioned Data. Retrieved from http://arxiv.org/abs/0803.1555v1
Theoretical advantages of lenient learners: An evolutionary game theoretic perspective (Journal article)
Panait, L., Tuyls, K., & Luke, S. (2008). Theoretical advantages of lenient learners: An evolutionary game theoretic perspective. Journal of Machine Learning Research, 9, 423-457.
Belief Networks for Bioinformatics (Journal article)
Donkers, J. H. H. L. M., & Tuyls, K. (2008). Belief Networks for Bioinformatics. Unknown Journal, 75-111. doi:10.1007/978-3-540-76803-6_3DOI: 10.1007/978-3-540-76803-6_3
Artificial agents learning human fairness (Conference Paper)
De Jong, S., Tuyls, K., & Verbeeck, K. (2008). Artificial agents learning human fairness. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS Vol. 2 (pp. 845-852).
EvOL-Neuron: Neuronal morphology generation (Journal article)
Torben-Nielsen, B., Tuyls, K., & Postma, E. (2008). EvOL-Neuron: Neuronal morphology generation. Neurocomputing, 71(4-6), 963-972. doi:10.1016/j.neucom.2007.02.016DOI: 10.1016/j.neucom.2007.02.016
Switching dynamics of multi-agent learning (Conference Paper)
Vrancx, P., Tuyls, K., Westra, R., & Nowe, A. (2008). Switching dynamics of multi-agent learning. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS Vol. 1 (pp. 302-309).
2007
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface (Book)
Tuyls, K., Westra, R., Saeys, Y., & Nowé, A. (2007). Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface (Vol. 4366 LNBI).
Static versus plastic controllers in evolutionary robotics (Conference Paper)
Van Lankveld, T., De Croon, G., & Tuyls, K. (2007). Static versus plastic controllers in evolutionary robotics. In Belgian/Netherlands Artificial Intelligence Conference (pp. 196-204).
The pattern memory of gene-protein networks (Conference Paper)
Westra, R. L., Hollanders, G., Bex, G. J., Gyssens, M., & Tuyls, K. (2007). The pattern memory of gene-protein networks. In AI Communications Vol. 20 (pp. 297-311).
Exploring selfish reinforcement learning in repeated games with stochastic rewards (Journal article)
Verbeeck, K., Nowé, A., Parent, J., & Tuyls, K. (2007). Exploring selfish reinforcement learning in repeated games with stochastic rewards. Autonomous Agents and Multi-Agent Systems, 14(3), 239-269. doi:10.1007/s10458-006-9007-0DOI: 10.1007/s10458-006-9007-0
Theoretical advantages of lenient Q-learners (Conference Paper)
Panait, L., & Tuyls, K. (2007). Theoretical advantages of lenient Q-learners. In Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems. ACM. doi:10.1145/1329125.1329173DOI: 10.1145/1329125.1329173
What evolutionary game theory tells us about multiagent learning (Journal article)
Tuyls, K., & Parsons, S. (2007). What evolutionary game theory tells us about multiagent learning. Artificial Intelligence, 171(7), 406-416. doi:10.1016/j.artint.2007.01.004DOI: 10.1016/j.artint.2007.01.004
Knowledge Discovery and Emergent Complexity in Bioinformatics (Conference Paper)
Westra, R., Tuyls, K., Saeys, Y., & Nowé, A. (2007). Knowledge Discovery and Emergent Complexity in Bioinformatics. In Unknown Conference (pp. 1-9). Springer Berlin Heidelberg. doi:10.1007/978-3-540-71037-0_1DOI: 10.1007/978-3-540-71037-0_1
Multi-agent Learning Dynamics: A Survey (Conference Paper)
van den Herik, H. J., Hennes, D., Kaisers, M., Tuyls, K., & Verbeeck, K. (2007). Multi-agent Learning Dynamics: A Survey. In Unknown Conference (pp. 36-56). Springer Berlin Heidelberg. doi:10.1007/978-3-540-75119-9_4DOI: 10.1007/978-3-540-75119-9_4
On Phase Transitions in Learning Sparse Networks (Conference Paper)
Hollanders, G., Bex, G. J., Gyssens, M., Westra, R. L., & Tuyls, K. (2007). On Phase Transitions in Learning Sparse Networks. In Unknown Conference (pp. 591-599). Springer Berlin Heidelberg. doi:10.1007/978-3-540-74958-5_57DOI: 10.1007/978-3-540-74958-5_57
On the Neuronal Morphology-Function Relationship: A Synthetic Approach (Conference Paper)
Torben-Nielsen, B., Tuyls, K., & Postma, E. O. (n.d.). On the Neuronal Morphology-Function Relationship: A Synthetic Approach. In Unknown Conference (pp. 131-144). Springer Berlin Heidelberg. doi:10.1007/978-3-540-71037-0_9DOI: 10.1007/978-3-540-71037-0_9
The Identification of Dynamic Gene-Protein Networks (Conference Paper)
Westra, R. L., Hollanders, G., Bex, G. J., Gyssens, M., & Tuyls, K. (2007). The Identification of Dynamic Gene-Protein Networks. In Unknown Conference (pp. 157-170). Springer Berlin Heidelberg. doi:10.1007/978-3-540-71037-0_11DOI: 10.1007/978-3-540-71037-0_11
2006
Hierarchical reinforcement learning with deictic representation in a computer game (Conference Paper)
Ponsen, M., Spronck, P., & Tuyls, K. (2006). Hierarchical reinforcement learning with deictic representation in a computer game. In Belgian/Netherlands Artificial Intelligence Conference.
Inference of Concise dtds from XML Data (Conference Paper)
Bex, G. J., Neven, F., Schwentick, T., & Tuyls, K. (2006). Inference of Concise dtds from XML Data. In Belgian/Netherlands Artificial Intelligence Conference.
Reconstruction of flexible gene-protein interaction networks using piecewise linear modeling and robust regression (Conference Paper)
Westra, R. L., Peeters, R. L. M., Hollanders, G., & Tuyls, K. (2006). Reconstruction of flexible gene-protein interaction networks using piecewise linear modeling and robust regression. In Proceedings of AISB'06: Adaptation in Artificial and Biological Systems Vol. 3 (pp. 180-188).
Reliable Instance Classifications in Law Enforcement (Conference Paper)
Vanderlooy, S., Postma, E., Tuyls, K., & Sprinkhuizen-Kuyper, I. (2006). Reliable Instance Classifications in Law Enforcement. In Belgian/Netherlands Artificial Intelligence Conference.
Towards robotic self-repair by means of neuronal remodelling (Conference Paper)
Torben-Nielsen, B., Tuyls, K., & Postma, E. O. (2006). Towards robotic self-repair by means of neuronal remodelling. In Proceedings of AISB'06: Adaptation in Artificial and Biological Systems Vol. 2 (pp. 138-144).
How to reach linguistic consensus: a proof of convergence for the naming game. (Journal article)
De Vylder, B., & Tuyls, K. (2006). How to reach linguistic consensus: a proof of convergence for the naming game.. Journal of theoretical biology, 242(4), 818-831. doi:10.1016/j.jtbi.2006.05.024DOI: 10.1016/j.jtbi.2006.05.024
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface (Book)
Tuyls, K., 'T Hoen, P. J., Verbeeck, K., & Sen, S. (2006). Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface (Vol. 3898 LNAI).
An Evolutionary Dynamical Analysis of Multi-Agent Learning in Iterated Games (Journal article)
Tuyls, K., Hoen, P. J. T., & Vanschoenwinkel, B. (2006). An Evolutionary Dynamical Analysis of Multi-Agent Learning in Iterated Games. Autonomous Agents and Multi-Agent Systems, 12(1), 115-153. doi:10.1007/s10458-005-3783-9DOI: 10.1007/s10458-005-3783-9
Inference of concise DTDs from XML data (Conference Paper)
Bex, G. J., Neven, F., Schwentick, T., & Tuyls, K. (2006). Inference of concise DTDs from XML data. In VLDB 2006 - Proceedings of the 32nd International Conference on Very Large Data Bases (pp. 115-126).
Robust and Scalable Coordination of Potential-Field Driven Agents (Conference Paper)
de Jong, S., Tuyls, K., & Sprinkhuizen-Kuyper, I. (2006). Robust and Scalable Coordination of Potential-Field Driven Agents. In 2006 International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (CIMCA'06). IEEE. doi:10.1109/cimca.2006.191DOI: 10.1109/cimca.2006.191
Shaping Realistic Neuronal Morphologies: An Evolutionary Computation Method (Conference Paper)
Torben-Nielsen, B., Tuyls, K., & Postma, E. O. (2006). Shaping Realistic Neuronal Morphologies: An Evolutionary Computation Method. In The 2006 IEEE International Joint Conference on Neural Network Proceedings. IEEE. doi:10.1109/ijcnn.2006.246733DOI: 10.1109/ijcnn.2006.246733
2005
An Evolutionary Game Theoretic Perspective on Learning in Mult-Agent Systems (Chapter)
Tuyls, K., Nowe, A., Lenaerts, T., & Manderick, B. (2004). An Evolutionary Game Theoretic Perspective on Learning in Mult-Agent Systems. In Information, Interaction and Agency (pp. 133-166). Springer Netherlands. doi:10.1007/1-4020-4094-6_5DOI: 10.1007/1-4020-4094-6_5
Coordinated exploration in multi-agent reinforcement learning: An application to load-balancing (Conference Paper)
Verbeeck, K., Nowé, A., & Tuyls, K. (2005). Coordinated exploration in multi-agent reinforcement learning: An application to load-balancing. In Proceedings of the International Conference on Autonomous Agents (pp. 1223-1224).
Multi-agent Reinforcement Learning in Stochastic Single and Multi-stage Games (Conference Paper)
Verbeeck, K., Nowé, A., Peeters, M., & Tuyls, K. (2005). Multi-agent Reinforcement Learning in Stochastic Single and Multi-stage Games. In Unknown Conference (pp. 275-294). Springer Berlin Heidelberg. doi:10.1007/978-3-540-32274-0_18DOI: 10.1007/978-3-540-32274-0_18
Preface (Conference Paper)
Verbeeck, K., Tuyls, K., Nowe, A., Kuijpers, B., & Manderick, B. (2005). Preface. In Belgian/Netherlands Artificial Intelligence Conference.
Towards a common lexicon in the naming game: The dynamics of synonymy reduction (Conference Paper)
De Vylder, B., & Tuyls, K. (2005). Towards a common lexicon in the naming game: The dynamics of synonymy reduction. In Belgian/Netherlands Artificial Intelligence Conference (pp. 112-119).
The evolutionary language game: an orthogonal approach. (Journal article)
Lenaerts, T., Jansen, B., Tuyls, K., & De Vylder, B. (2005). The evolutionary language game: an orthogonal approach.. Journal of theoretical biology, 235(4), 566-582. doi:10.1016/j.jtbi.2005.02.009DOI: 10.1016/j.jtbi.2005.02.009
Evolutionary game theory and multi-agent reinforcement learning (Journal article)
TUYLS, K., & NOWÉ, A. N. N. (2005). Evolutionary game theory and multi-agent reinforcement learning. The Knowledge Engineering Review, 20(1), 63-90. doi:10.1017/s026988890500041xDOI: 10.1017/s026988890500041x
2004
An Evolutionary Game Theoretic Perspective on Learning in Multi-Agent Systems (Journal article)
Tuyls, K., Nowe, A., Lenaerts, T., & Manderick, B. (2004). An Evolutionary Game Theoretic Perspective on Learning in Multi-Agent Systems. Synthese, 139(2), 297-330. doi:10.1023/b:synt.0000024908.89191.f1DOI: 10.1023/b:synt.0000024908.89191.f1
Analyzing multi-agent reinforcement learning using evolutionary dynamics (Conference Paper)
'T Hoen, P. J., & Tuyls, K. (2004). Analyzing multi-agent reinforcement learning using evolutionary dynamics. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) Vol. 3201 (pp. 168-179).
2003
A selection-mutation model for q-learning in multi-agent systems (Conference Paper)
Tuyls, K., Verbeeck, K., & Lenaerts, T. (2003). A selection-mutation model for q-learning in multi-agent systems. In Proceedings of the second international joint conference on Autonomous agents and multiagent systems. ACM. doi:10.1145/860575.860687DOI: 10.1145/860575.860687
Extended Replicator Dynamics as a Key to Reinforcement Learning in Multi-agent Systems (Conference Paper)
Tuyls, K., Heytens, D., Nowe, A., & Manderick, B. (2003). Extended Replicator Dynamics as a Key to Reinforcement Learning in Multi-agent Systems. In Unknown Conference (pp. 421-431). Springer Berlin Heidelberg. doi:10.1007/978-3-540-39857-8_38DOI: 10.1007/978-3-540-39857-8_38
On a Dynamical Analysis of Reinforcement Learning in Games: Emergence of Occam’s Razor (Conference Paper)
Tuyls, K., Verbeeck, K., & Maes, S. (n.d.). On a Dynamical Analysis of Reinforcement Learning in Games: Emergence of Occam’s Razor. In Unknown Conference (pp. 335-344). Springer Berlin Heidelberg. doi:10.1007/3-540-45023-8_32DOI: 10.1007/3-540-45023-8_32
Reinforcement Learning in Large State Spaces (Conference Paper)
Tuyls, K., Maes, S., & Manderick, B. (2003). Reinforcement Learning in Large State Spaces. In Unknown Conference (pp. 319-326). Springer Berlin Heidelberg. doi:10.1007/978-3-540-45135-8_27DOI: 10.1007/978-3-540-45135-8_27
2000
Claes, D., Robbel, P., Oliehoek, F., Tuyls, K., Hennes, D., & Van der Hoek, W. (n.d.). Effective Approximations for Multi Robot Coordination in Spatially Distributed Tasks. In AAMAS 2015.