Photo of Prof Karl Tuyls

Prof Karl Tuyls PhD, FBCS

Professor School of Electrical Engineering, Electronics and Computer Science

Publications

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.

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.

Evolving Indoor Navigational Strategies Using Gated Recurrent Units In NEAT (Journal article)

Butterworth, J., Savani, R., & Tuyls, K. (n.d.). Evolving Indoor Navigational Strategies Using Gated Recurrent Units In NEAT. Retrieved from http://arxiv.org/abs/1904.06239v1

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/s10458-019-09411-3

DOI: 10.1007/s10458-019-09411-3

alpha-Rank: Multi-Agent Evaluation by Evolution (Journal article)

Omidshafiei, S., Papadimitriou, C., Piliouras, G., Tuyls, K., Rowland, M., Lespiau, J. -B., . . . Munos, R. (2019). alpha-Rank: Multi-Agent Evaluation by Evolution. SCIENTIFIC REPORTS, 9. doi:10.1038/s41598-019-45619-9

DOI: 10.1038/s41598-019-45619-9

2018

A Comparative Study of Bug Algorithms for Robot Navigation (Journal article)

McGuire, K., Croon, G. D., & Tuyls, K. (n.d.). A Comparative Study of Bug Algorithms for Robot Navigation. Retrieved from http://arxiv.org/abs/1808.05050v2

A Generalised Method for Empirical Game Theoretic Analysis (Journal article)

Tuyls, K., Perolat, J., Lanctot, M., Leibo, J. Z., Graepel, T., & ACM. (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 http://gateway.webofknowledge.com/

Actor-Critic Policy Optimization in Partially Observable Multiagent Environments (Journal article)

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/

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/

Emergence of Linguistic Communication from Referential Games with Symbolic and Pixel Input (Conference Paper)

Lazaridou, A., Hermann, K. M., Tuyls, K., & Clark, S. (n.d.). Emergence of Linguistic Communication from Referential Games with Symbolic and Pixel Input. Retrieved from http://arxiv.org/abs/1804.03984v1

Emergent Communication through Negotiation (Journal article)

Cao, K., Lazaridou, A., Lanctot, M., Leibo, J. Z., Tuyls, K., & Clark, S. (n.d.). Emergent Communication through Negotiation. Retrieved from http://arxiv.org/abs/1804.03980v1

Experience Selection in Deep Reinforcement Learning for Control (Journal article)

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 http://gateway.webofknowledge.com/

Inequity aversion improves cooperation in intertemporal social dilemmas (Journal article)

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/

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.2018.2800101

DOI: 10.1109/LRA.2018.2800101

Lenient Multi-Agent Deep Reinforcement Learning (Journal article)

Palmer, G., Tuyls, K., Bloembergen, D., Savani, R., & ACM. (2018). Lenient Multi-Agent Deep Reinforcement Learning. PROCEEDINGS OF THE 17TH INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS AND MULTIAGENT SYSTEMS (AAMAS' 18), 443-451. 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/s10514-018-9726-5

DOI: 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_1

DOI: 10.1007/978-3-030-01713-2_1

Re-evaluating Evaluation (Journal article)

Balduzzi, D., Tuyls, K., Perolat, J., & Graepel, T. (2018). Re-evaluating Evaluation. ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 31 (NIPS 2018), 31. Retrieved from http://gateway.webofknowledge.com/

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.v39i4.2824

DOI: 10.1609/aimag.v39i4.2824

SCC-rFMQ Learning in Cooperative Markov Games with Continuous Actions (Conference Paper)

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

Space Debris Removal: Learning to Cooperate and the Price of Anarchy (Journal article)

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.2018.00054

DOI: 10.3389/frobt.2018.00054

Symmetric Decomposition of Asymmetric Games (Journal article)

Tuyls, K., Perolat, J., Lanctot, M., Ostrovski, G., Savani, R., Leibo, J. Z., . . . Legg, S. (2018). Symmetric Decomposition of Asymmetric Games. SCIENTIFIC REPORTS, 8. doi:10.1038/s41598-018-19194-4

The Mechanics of n-Player Differentiable Games (Conference Paper)

Balduzzi, D., Racaniere, S., Martens, J., Foerster, J., Tuyls, K., & Graepel, T. (n.d.). The Mechanics of n-Player Differentiable Games. In PMLR volume 80, 2018. Retrieved from http://arxiv.org/abs/1802.05642v2

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).

2017

A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning (Journal article)

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/

A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning. (Conference Paper)

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. 4193-4206). Retrieved from http://www.informatik.uni-trier.de/~ley/db/conf/nips/nips2017.html

A multi-agent reinforcement learning model of common-pool resource appropriation (Journal article)

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/

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. 3646-3655). Retrieved from http://www.informatik.uni-trier.de/~ley/db/conf/nips/nips2017.html

Decentralised Online Planning for Multi-Robot Warehouse Commissioning (Conference Paper)

Claes, D., Oliehoek, F., Baier, H., Tuyls, K., & Machinery, A. C. (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 http://gateway.webofknowledge.com/

Environmental effects on simulated emotional and moody agents (Journal article)

Collenette, J., Atkinson, K., Bloembergen, D., & Tuyls, K. (2017). Environmental effects on simulated emotional and moody agents. KNOWLEDGE ENGINEERING REVIEW, 32. doi:10.1017/S0269888917000170

DOI: 10.1017/S0269888917000170

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).

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/

2016

A Telepresence-Robot Approach for Efficient Coordination of Swarms (Conference Paper)

Tuyls, K., Alers, S., Cucco, E., Claes, D., & Bloembergen, D. (2016, July 4). A Telepresence-Robot Approach for Efficient Coordination of Swarms. In The 15th International Conference on the Synthesis and Simulation of Living Systems (Alife). Cancun, Mexico.

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:10.5220/0005768601340142

DOI: 10.5220/0005768601340142

Efficient Optical flow and Stereo Vision for Velocity Estimation and Obstacle Avoidance on an Autonomous Pocket Drone. (Journal article)

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.

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-160814

DOI: 10.3233/IDA-160814

Improved Deep Reinforcement Learning for Robotics Through Distribution-based Experience Retention (Conference Paper)

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.

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).

Local histogram matching for efficient optical flow computation applied to velocity estimation on pocket drones. (Conference Paper)

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 http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7478842

On the prevalence of hierarchies in social networks (Journal article)

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/s13278-016-0363-8

DOI: 10.1007/s13278-016-0363-8

Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems. (Book)

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.

Socially-Aware Multiagent Learning: Towards Socially Optimal Outcomes (Conference Paper)

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:10.3233/978-1-61499-672-9-533

DOI: 10.3233/978-1-61499-672-9-533

Space Debris Removal: A Game Theoretic Analysis (Conference Paper)

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:10.3233/978-1-61499-672-9-1658

DOI: 10.3233/978-1-61499-672-9-1658

Space Debris Removal: A Game Theoretic Analysis (Journal article)

Klima, R., Bloembergen, D., Savani, R., Tuyls, K., Hennes, D., & Izzo, D. (2016). Space Debris Removal: A Game Theoretic Analysis. Games, 7(3), 20. doi:10.3390/g7030020

DOI: 10.3390/g7030020

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

The Effect of Mobility and Emotion on Interactions in Multi-Agent Systems (Conference Paper)

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:10.3233/978-1-61499-682-8-39

DOI: 10.3233/978-1-61499-682-8-39

Using transfer learning to model unknown opponents in automated negotiations (Conference Paper)

Chen, S., Zhou, S., Weiss, G., & Tuyls, K. (2016). Using transfer learning to model unknown opponents in automated negotiations. In Studies in Computational Intelligence Vol. 638 (pp. 175-192). doi:10.1007/978-3-319-30307-9_11

DOI: 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., & IEEE. (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 http://gateway.webofknowledge.com/

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: Principles and Applications (pp. 273-299). doi:10.1016/B978-0-08-100249-0.00013-6

DOI: 10.1016/B978-0-08-100249-0.00013-6

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., & ACM. (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 http://gateway.webofknowledge.com/

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

Evolutionary Dynamics of Multi-Agent Learning: A Survey (Journal article)

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.4818

DOI: 10.1613/jair.4818

Factored four way conditional restricted Boltzmann machines for activity recognition (Journal article)

Mocanu, D. C., 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.2015.01.013

DOI: 10.1016/j.patrec.2015.01.013

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_30

DOI: 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_5

DOI: 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_8

DOI: 10.1007/978-3-319-22416-9_8

Learning in Networked Interactions: A Replicator Dynamics Approach (Journal article)

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_4

DOI: 10.1007/978-3-319-18084-7_4

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:10.1145/2774224

DOI: 10.1145/2774224

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., & ACM. (2015). Multi-Agent Target Tracking using Particle Filters enhanced with Context Data. Poster session presented at the meeting of Unknown Conference. Retrieved from http://gateway.webofknowledge.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_10

DOI: 10.1007/978-3-319-18084-7_10

Multi-source entity resolution for genealogical data (Chapter)

Efremova, J., Calders, T., & Weiss, G. (2015). Multi-source entity resolution for genealogical data. In Population Reconstruction (pp. 129-154). doi:10.1007/978-3-319-19884-2_7

DOI: 10.1007/978-3-319-19884-2_7

On the Skewed Degree Distribution of Hierarchical Networks (Conference Paper)

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:10.1145/2808797.2809409

DOI: 10.1145/2808797.2809409

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.

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., & ACM. (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 http://gateway.webofknowledge.com/

Survival of the Chartist: An Evolutionary Agent-Based Analysis of Stock Market Trading (Conference Paper)

Bloembergen, D., Hennes, D., Parsons, S., Tuyls, K., & ACM. (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 http://gateway.webofknowledge.com/

Towards autonomous robotic systems: 16th annual conference, TAROS 2015 Liverpool, UK, September 8-10, 2015 proceedings (Conference Paper)

Dixon, C., & Tuyls, K. (2015). Towards autonomous robotic systems: 16th annual conference, TAROS 2015 Liverpool, UK, September 8-10, 2015 proceedings. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 9287. doi:10.1007/978-3-319-22416-9

DOI: 10.1007/978-3-319-22416-9

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:10.1080/09540091.2015.1039492

DOI: 10.1080/09540091.2015.1039492

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_12

DOI: 10.1007/978-3-319-18615-3_12

2014

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/s10458-013-9240-2

DOI: 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., & Machinery, A. C. (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 http://gateway.webofknowledge.com/

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/s13218-013-0286-8

DOI: 10.1007/s13218-013-0286-8

Biologically Inspired Multi-Robot Foraging (Conference Paper)

Alers, S., Claes, D., Tuyls, K., Weiss, G., & Machinery, A. C. (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 http://gateway.webofknowledge.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).

Evolution of Cooperation in Arbitrary Complex Networks (Conference Paper)

Ranjbar-Sahraei, B., Ammar, H. B., Bloembergen, D., Tuyls, K., Weiss, G., & Machinery, A. C. (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 http://gateway.webofknowledge.com/

How to Win RoboCup@Work? The Swarmlab@Work Approach Revealed (Conference Paper)

Alers, S., Claes, D., Fossel, J., Hennes, D., Tuyls, K., & Weiss, G. (2014). How to Win RoboCup@Work? The Swarmlab@Work Approach Revealed. In ROBOCUP 2013: ROBOT WORLD CUP XVII Vol. 8371 (pp. 147-158). Retrieved from http://gateway.webofknowledge.com/

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:10.3233/978-1-61499-419-0-105

DOI: 10.3233/978-1-61499-419-0-105

Learning to Reach Agreement in a Continuous Ultimatum Game (Journal article)

Jong, S. D., Uyttendaele, S., & Tuyls, K. (n.d.). Learning to Reach Agreement in a Continuous Ultimatum Game. Journal Of Artificial Intelligence Research, Volume 33, pages 551-574, 2008. doi:10.1613/jair.2685

DOI: 10.1613/jair.2685

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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 8732 (pp. 41-56).

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:10.3233/978-1-61499-419-0-983

DOI: 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 National Conference on Artificial Intelligence Vol. 2 (pp. 1471-1477).

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.

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-x

DOI: 10.1007/s13218-013-0284-x

2013

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).

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.

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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 8189 LNAI (pp. 449-464). doi:10.1007/978-3-642-40991-2_29

DOI: 10.1007/978-3-642-40991-2_29

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).

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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 8103 LNAI (pp. 108-120). doi:10.1007/978-3-642-40849-6-10

DOI: 10.1007/978-3-642-40849-6-10

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).

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 2013 - Conference Proceedings (pp. 179-188). doi:10.1109/ICUAS.2013.6564688

DOI: 10.1109/ICUAS.2013.6564688

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 Communications in Computer and Information Science Vol. 271 (pp. 382-396). doi:10.1007/978-3-642-29966-7_25

DOI: 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).

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 2013 (pp. 436-441). doi:10.1109/ICMECH.2013.6518576

DOI: 10.1109/ICMECH.2013.6518576

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).

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 IEEE International Conference on Intelligent Robots and Systems (pp. 1192-1198). doi:10.1109/IROS.2012.6386125

DOI: 10.1109/IROS.2012.6386125

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.2012.048871

DOI: 10.1504/IJCNDS.2012.048871

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 GECCO'12 - Proceedings of the 14th International Conference on Genetic and Evolutionary Computation (pp. 943-949). doi:10.1145/2330163.2330294

DOI: 10.1145/2330163.2330294

Evolutionary dynamics of ant colony optimization (Conference Paper)

Bou Ammar, H., Tuyls, K., & Kaisers, M. (2012). Evolutionary dynamics of ant colony optimization. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 7598 LNAI (pp. 40-52). doi:10.1007/978-3-642-33690-4_6

DOI: 10.1007/978-3-642-33690-4_6

Multi-agent learning and the reinforcement gradient (Conference Paper)

Kaisers, M., Bloembergen, D., & Tuyls, K. (2012). Multi-agent learning and the reinforcement gradient. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 7541 LNAI (pp. 145-159). doi:10.1007/978-3-642-34799-3-10

DOI: 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).

Preface (Book)

Cossentino, M., Kaisers, M., Tuyls, K., & Weiss, G. (2012). Preface (Vol. 7541 LNAI).

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.2012.07.001

DOI: 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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 7541 LNAI (pp. 1-16). doi:10.1007/978-3-642-34799-3-1

DOI: 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).

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/S0219525911500251

DOI: 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.

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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 7598 LNAI (pp. 106-115). doi:10.1007/978-3-642-33690-4_11

DOI: 10.1007/978-3-642-33690-4_11

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.

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).

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.

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).

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).

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/s10458-010-9122-9

DOI: 10.1007/s10458-010-9122-9

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.

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).

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.

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).

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.

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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 5924 LNAI (pp. 1-32). doi:10.1007/978-3-642-11814-2_1

DOI: 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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 5924 LNAI (pp. 60-73). doi:10.1007/978-3-642-11814-2_4

DOI: 10.1007/978-3-642-11814-2_4

Evolutionary dynamics of regret minimization (Conference Paper)

Klos, T., Van Ahee, G. J., & Tuyls, K. (2010). Evolutionary dynamics of regret minimization. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 6322 LNAI (pp. 82-96). doi:10.1007/978-3-642-15883-4_6

DOI: 10.1007/978-3-642-15883-4_6

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).

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. Studies in Computational Intelligence, 281, 45-63. doi:10.1007/978-3-642-11688-9_2

DOI: 10.1007/978-3-642-11688-9_2

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).

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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 5924 LNAI (pp. 49-59). doi:10.1007/978-3-642-11814-2_3

DOI: 10.1007/978-3-642-11814-2_3

Reports of the AAAI 2010 conference workshops (Conference Paper)

Aha, D. W., Boddy, M., Bulitko, V., D'Avila Garcez, A. S., Doshi, P., Edelkamp, S., . . . Van Der Meyden, R. (2010). Reports of the AAAI 2010 conference workshops. In AI Magazine Vol. 31 (pp. 95-104).

Stigmergic landmark routing: A routing algorithm for wireless mobile Ad-Hoc networks (Conference Paper)

Lemmens, N., & Tuyls, K. (2010). Stigmergic landmark routing: A routing algorithm for wireless mobile Ad-Hoc networks. In Proceedings of the 12th Annual Genetic and Evolutionary Computation Conference, GECCO '10 (pp. 471-478). doi:10.1145/1830483.1830491

DOI: 10.1145/1830483.1830491

2009

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.2009.09.002

DOI: 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).

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).

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

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).

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 Proceedings - 2008 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2008 (pp. 447-450). doi:10.1109/WIIAT.2008.261

DOI: 10.1109/WIIAT.2008.261

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).

Bee behaviour in multi-agent systems (a bee foraging algorithm) (Conference Paper)

Lemmens, N., De Jong, S., Tuyls, K., & Nowé, A. (2008). Bee behaviour in multi-agent systems (a bee foraging algorithm). In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 4865 LNAI (pp. 145-156). doi:10.1007/978-3-540-77949-0_11

DOI: 10.1007/978-3-540-77949-0_11

Belief networks for bioinformatics (Journal article)

Donkers, J. H. H. L. M., & Tuyls, K. (2008). Belief networks for bioinformatics. Studies in Computational Intelligence, 94, 75-111. doi:10.1007/978-3-540-76803-6_3

DOI: 10.1007/978-3-540-76803-6_3

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).

Entertainment computing in the orbit (Conference Paper)

Rauterberg, M., Neerincx, M., Tuyls, K., & van Loon, J. (2008). Entertainment computing in the orbit. In IFIP International Federation for Information Processing Vol. 279 (pp. 59-70). doi:10.1007/978-0-387-09701-5_6

DOI: 10.1007/978-0-387-09701-5_6

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.2007.02.016

DOI: 10.1016/j.neucom.2007.02.016

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(02). doi:10.1017/S026988890800132X

DOI: 10.1017/S026988890800132X

Formalizing multi-state learning dynamics (Conference Paper)

Hennes, D., Tuyls, K., & Rauterberg, M. (2008). Formalizing multi-state learning dynamics. In Proceedings - 2008 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2008 (pp. 266-272). doi:10.1109/WIIAT.2008.33

DOI: 10.1109/WIIAT.2008.33

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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 4865 LNAI (pp. 117-128). doi:10.1007/978-3-540-77949-0_9

DOI: 10.1007/978-3-540-77949-0_9

Privacy Preserving ID3 over Horizontally, Vertically and Grid Partitioned Data (Journal article)

Kuijpers, B., Lemmens, V., Moelans, B., & Tuyls, K. (n.d.). Privacy Preserving ID3 over Horizontally, Vertically and Grid Partitioned Data. Retrieved from http://arxiv.org/abs/0803.1555v1

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).

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).

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).

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.

2007

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/s10458-006-9007-0

DOI: 10.1007/s10458-006-9007-0

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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 4366 LNBI (pp. 1-9).

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).

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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 4676 LNAI (pp. 36-56).

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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 4701 LNAI (pp. 591-599).

On the neuronal morphology-function relationship: A synthetic approach (Conference Paper)

Torben-Nielsen, B., Tuyls, K., & Postma, E. O. (2007). On the neuronal morphology-function relationship: A synthetic approach. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 4366 LNBI (pp. 131-144).

Robust and scalable coordination of potential-field driven agents (Conference Paper)

De Jong, S., Tuyls, K., & Sprinkhuizen-Kuyper, I. (2007). Robust and scalable coordination of potential-field driven agents. In CIMCA 2006: International Conference on Computational Intelligence for Modelling, Control and Automation, Jointly with IAWTIC 2006: International Conference on Intelligent Agents Web Technologies .... doi:10.1109/CIMCA.2006.191

DOI: 10.1109/CIMCA.2006.191

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 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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 4366 LNBI (pp. 157-170).

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).

Theoretical advantages of lenient Q-learners: An evolutionary game theoretic perspective (Conference Paper)

Panait, L., & Tuyls, K. (2007). Theoretical advantages of lenient Q-learners: An evolutionary game theoretic perspective. In Proceedings of the International Conference on Autonomous Agents (pp. 180-187). doi:10.1145/1329125.1329173

DOI: 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.2007.01.004

DOI: 10.1016/j.artint.2007.01.004

2006

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/s10458-005-3783-9

DOI: 10.1007/s10458-005-3783-9

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.

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.2006.05.024

DOI: 10.1016/j.jtbi.2006.05.024

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.

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).

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).

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.

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 IEEE International Conference on Neural Networks - Conference Proceedings (pp. 573-580).

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).

2005

An evolutionary game theoretic perspective on learning in mult-agent systems (Chapter)

Tuyls, K., Nowe, A., Lenaerts, T., & Manderick, B. (2005). An evolutionary game theoretic perspective on learning in mult-agent systems. In Information, Interaction, and Agency (pp. 133-166). doi:10.1007/1-4020-4094-6_5

DOI: 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).

Evolutionary game theory and multi-agent reinforcement learning (Journal article)

TUYLS, K., & NOWÉ, A. (2005). Evolutionary game theory and multi-agent reinforcement learning. The Knowledge Engineering Review, 20(01), 63. doi:10.1017/S026988890500041X

DOI: 10.1017/S026988890500041X

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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 3394 LNAI (pp. 275-294). doi:10.1007/978-3-540-32274-0_18

DOI: 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.

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.2005.02.009

DOI: 10.1016/j.jtbi.2005.02.009

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).

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.f1

DOI: 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 Interantional Conference on Autonomous Agents Vol. 2 (pp. 693-700).

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 Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) Vol. 2837 (pp. 421-431).

On a dynamical analysis of reinforcement learning in games: Emergence of occam's razor (Conference Paper)

Tuyls, K., Verbeeck, K., & Maes, S. (2003). On a dynamical analysis of reinforcement learning in games: Emergence of occam's razor. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) Vol. 2691 (pp. 335-344).

Reinforcement learning in large state spaces simulated robotic soccer as a testbed (Conference Paper)

Tuyls, K., Maes, S., & Manderick, B. (2003). Reinforcement learning in large state spaces simulated robotic soccer as a testbed. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) Vol. 2752 (pp. 319-326).

2000

Effective Approximations for Multi Robot Coordination in Spatially Distributed Tasks (Conference Paper)

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.