Karl Tuyls

Nyree Lemmens, Karl Tuyls: Stigmergic Landmark Optimization. Advances in Complex Systems 15(8) (2012)

Karl Tuyls, Gerhard Weiss: Multiagent Learning: Basics, Challenges, and Prospects. AI Magazine 33(3): 41-52 (2012)

Mihail Mihaylov, Yann-Aël Le Borgne, Karl Tuyls, Ann Nowé: Decentralised reinforcement learning for energy-efficient scheduling in wireless sensor networks. IJCNDS 9(3/4): 207-224 (2012)

Daniel Hennes, Daniel Claes, Wim Meeussen, Karl Tuyls: Multi-robot collision avoidance with localization uncertainty. AAMAS 2012: 147-154

Haitham Bou-Ammar, Karl Tuyls, Matthew E. Taylor, Kurt Driessens, Gerhard Weiss: Reinforcement learning transfer via sparse coding. AAMAS 2012: 383-390

Michael Kaisers, Daan Bloembergen, Karl Tuyls: A common gradient in multi-agent reinforcement learning. AAMAS 2012: 1393-1394

Sjriek Alers, Daan Bloembergen, Max Bügler, Daniel Hennes, Karl Tuyls: MITRO: an augmented mobile telepresence robot with assisted control (demonstration). AAMAS 2012: 1475-1476

Daniel Claes, Daniel Hennes, Wim Meeussen, Karl Tuyls: CALU: collision avoidance with localization uncertainty (demonstration). AAMAS 2012: 1495-1496

Daniel Hennes, Daan Bloembergen, Michael Kaisers, Karl Tuyls, Simon Parsons: Evolutionary advantage of foresight in markets. GECCO 2012: 943-950

Daniel Claes, Daniel Hennes, Karl Tuyls, Wim Meeussen: Collision avoidance under bounded localization uncertainty. IROS 2012: 1192-1198

Haitham Bou-Ammar, Karl Tuyls, Michael Kaisers: Evolutionary Dynamics of Ant Colony Optimization. MATES 2012: 40-52

Marcel Neumann, Karl Tuyls, Michael Kaisers: Using Time as a Strategic Element in Continuous Double Auctions. MATES 2012: 106-115

Massimo Cossentino, Michael Kaisers, Karl Tuyls, Gerhard Weiss (Eds.): Multi-Agent Systems - 9th European Workshop, EUMAS 2011, Maastricht, The Netherlands, November 14-15, 2011. Revised Selected Papers. Lecture Notes in Computer Science 7541, Springer 2012, isbn 978-3-642-34798-6

Steven de Jong, Karl Tuyls: Human-inspired computational fairness. Autonomous Agents and Multi-Agent Systems 22(1): 103-126 (2011)

Michael Kaisers, Karl Tuyls: FAQ-Learning in Matrix Games: Demonstrating Convergence Near Nash Equilibria, and Bifurcation of Attractors in the Battle of Sexes. Interactive Decision Theory and Game Theory 2011

Mihail Mihaylov, Yann-Aël Le Borgne, Karl Tuyls, Ann Nowé: Distributed cooperation in wireless sensor networks. AAMAS 2011: 249-256

Steven de Jong, Daniel Hennes, Karl Tuyls, Ya'akov (Kobi) Gal: Metastrategies in the Colored Trails game. AAMAS 2011: 551-558

Daan Bloembergen, Michael Kaisers, Karl Tuyls: Empirical and theoretical support for lenient learning. AAMAS 2011: 1105-1106

Sjriek Alers, Daan Bloembergen, Daniel Hennes, Steven de Jong, Michael Kaisers, Nyree Lemmens, Karl Tuyls, Gerhard Weiss: Bee-inspired foraging in an embodied swarm. AAMAS 2011: 1311-1312

Haitham Bou-Ammar, Matthew E. Taylor, Karl Tuyls, Gerhard Weiss: Reinforcement Learning Transfer Using a Sparse Coded Inter-task Mapping. EUMAS 2011: 1-16

Michael Kaisers, Daan Bloembergen, Karl Tuyls: Multi-agent Learning and the Reinforcement Gradient. EUMAS 2011: 145-159

Mihail Mihaylov, Yann-Aël Le Borgne, Ann Nowé, Karl Tuyls: Self-organizing Synchronicity and Desynchronicity using Reinforcement Learning. ICAART (2) 2011: 94-103

David W. Aha, Mark S. Boddy, Vadim Bulitko, Artur S. d'Avila Garcez, Prashant Doshi, Stefan Edelkamp, Christopher W. Geib, Piotr J. Gmytrasiewicz, Robert P. Goldman, Pascal Hitzler, Charles L. Isbell, Darsana P. Josyula, Leslie Pack Kaelbling, Kristian Kersting, Maithilee Kunda, Luís C. Lamb, Bhaskara Marthi, Keith McGreggor, Vivi Nastase, Gregory Provan, Anita Raja, Ashwin Ram, Mark O. Riedl, Stuart J. Russell, Ashish Sabharwal, Jan-Georg Smaus, Gita Sukthankar, Karl Tuyls, Ron van der Meyden, Alon Y. Halevy, Lilyana Mihalkova, Sriraam Natarajan: Reports of the AAAI 2010 Conference Workshops. AI Magazine 31(4): 95-108 (2010)

Michael Kaisers, Karl Tuyls: Frequency adjusted multi-agent Q-learning. AAMAS 2010: 309-316

Nyree Lemmens, Karl Tuyls: Stigmergic landmark routing: a routing algorithm for wireless mobile ad-hoc networks. GECCO 2010: 47-54

Tomas Klos, Gerrit Jan van Ahee, Karl Tuyls: Evolutionary Dynamics of Regret Minimization. ECML/PKDD (2) 2010: 82-96

Marc J. V. Ponsen, Tom Croonenborghs, Karl Tuyls, Jan Ramon, Kurt Driessens, H. Jaap van den Herik, Eric O. Postma: Learning with Whom to Communicate Using Relational Reinforcement Learning. Interactive Collaborative Information Systems 2010: 45-63

Matthew E. Taylor, Karl Tuyls (Eds.): Adaptive and Learning Agents, Second Workshop, ALA 2009, Held as Part of the AAMAS 2009 Conference in Budapest, Hungary, May 12, 2009, Revised Selected Papers. Lecture Notes in Computer Science 5924, Springer 2010, isbn 978-3-642-11813-5

Marc J. V. Ponsen, Matthew E. Taylor, Karl Tuyls: Abstraction and Generalization in Reinforcement Learning: A Summary and Framework. ALA 2009: 1-32

Michael Kaisers, Karl Tuyls: Replicator Dynamics for Multi-agent Learning: An Orthogonal Approach. ALA 2009: 49-59

Mihail Mihaylov, Karl Tuyls, Ann Nowé: Decentralized Learning in Wireless Sensor Networks. ALA 2009: 60-73

Nyree Lemmens, Karl Tuyls: Stigmergic landmark foraging. AAMAS (1) 2009: 497-504

Daniel Hennes, Karl Tuyls, Matthias Rauterberg: State-coupled replicator dynamics. AAMAS (2) 2009: 789-796

Steven de Jong, Karl Tuyls: Learning to cooperate in a continuous tragedy of the commons. AAMAS (2) 2009: 1185-1186

Marc J. V. Ponsen, Tom Croonenborghs, Karl Tuyls, Jan Ramon, Kurt Driessens: Learning with whom to communicate using relational reinforcement learning. AAMAS (2) 2009: 1221-1222

Michael Kaisers, Karl Tuyls, Simon Parsons, Frank Thuijsman: An evolutionary model of multi-agent learning with a varying exploration rate. AAMAS (2) 2009: 1255-1256

Ben Torben-Nielsen, Karl Tuyls, Eric O. Postma: EvOL-Neuron: Neuronal morphology generation. Neurocomputing 71(4-6): 963-972 (2008)

Steven de Jong, Simon Uyttendaele, Karl Tuyls: Learning to Reach Agreement in a Continuous Ultimatum Game. J. Artif. Intell. Res. (JAIR) 33: 551-574 (2008)

Liviu Panait, Karl Tuyls, Sean Luke: Theoretical Advantages of Lenient Learners: An Evolutionary Game Theoretic Perspective. Journal of Machine Learning Research 9: 423-457 (2008)

Steven de Jong, Karl Tuyls, Katja Verbeeck: Fairness in multi-agent systems. Knowledge Eng. Review 23(2): 153-180 (2008)

Marc J. V. Ponsen, Jan Ramon, Tom Croonenborghs, Kurt Driessens, Karl Tuyls: Bayes-Relational Learning of Opponent Models from Incomplete Information in No-Limit Poker. AAAI 2008: 1485-1486

Peter Vrancx, Karl Tuyls, Ronald L. Westra: Switching dynamics of multi-agent learning. AAMAS (1) 2008: 307-313

Steven de Jong, Karl Tuyls, Katja Verbeeck: Artificial agents learning human fairness. AAMAS (2) 2008: 863-870

Daniel Hennes, Karl Tuyls, Matthias Rauterberg: Formalizing Multi-state Learning Dynamics. IAT 2008: 266-272

Michael Kaisers, Karl Tuyls, Frank Thuijsman, Simon Parsons: Auction Analysis by Normal Form Game Approximation. IAT 2008: 447-450

Karl Tuyls, Ann Nowé: Introduction to Game Theory. Wiley Encyclopedia of Computer Science and Engineering 2008

H. H. L. M. Donkers, Karl Tuyls: Belief Networks for Bioinformatics. Computational Intelligence in Bioinformatics 2008: 75-111

Karl Tuyls, Ann Nowé, Zahia Guessoum, Daniel Kudenko (Eds.): Adaptive Agents and Multi-Agent Systems III. Adaptation and Multi-Agent Learning, 5th, 6th, and 7th European Symposium, ALAMAS 2005-2007 on Adaptive and Learning Agents and Multi-Agent Systems, Revised Selected Papers. Lecture Notes in Computer Science 4865, Springer 2008, isbn 978-3-540-77947-6

Bart Kuijpers, Vanessa Lemmens, Bart Moelans, Karl Tuyls: Privacy Preserving ID3 over Horizontally, Vertically and Grid Partitioned Data. CoRR abs/0803.1555 (2008)

Katja Verbeeck, Ann Nowé, Johan Parent, Karl Tuyls: Exploring selfish reinforcement learning in repeated games with stochastic rewards. Autonomous Agents and Multi-Agent Systems 14(3): 239-269 (2007)

Karl Tuyls, Simon Parsons: What evolutionary game theory tells us about multiagent learning. Artif. Intell. 171(7): 406-416 (2007)

Ronald L. Westra, Goele Hollanders, Geert Jan Bex, Marc Gyssens, Karl Tuyls: The pattern memory of gene-protein networks. AI Commun. 20(4): 297-311 (2007)

Steven de Jong, Karl Tuyls, Katja Verbeeck, Nico Roos: Priority Awareness: Towards a Computational Model of Human Fairness for Multi-agent Systems. Adaptive Agents and Multi-Agents Systems 2007: 117-128

Nyree Lemmens, Steven de Jong, Karl Tuyls, Ann Nowé: Bee Behaviour in Multi-agent Systems. Adaptive Agents and Multi-Agents Systems 2007: 145-156

Liviu Panait, Karl Tuyls: Theoretical advantages of lenient Q-learners: an evolutionary game theoretic perspective. AAMAS 2007: 40

H. Jaap van den Herik, Daniel Hennes, Michael Kaisers, Karl Tuyls, Katja Verbeeck: Multi-agent Learning Dynamics: A Survey. CIA 2007: 36-56

Goele Hollanders, Geert Jan Bex, Marc Gyssens, Ronald L. Westra, Karl Tuyls: On Phase Transitions in Learning Sparse Networks. ECML 2007: 591-599

Karl Tuyls, Ronald L. Westra, Yvan Saeys, Ann Nowé (Eds.): Knowledge Discovery and Emergent Complexity in Bioinformatics, First International Workshop, KDECB 2006, Ghent, Belgium, May 10, 2006. Revised Selected Papers. Lecture Notes in Computer Science 4366, Springer 2007, isbn 978-3-540-71036-3

Karl Tuyls, Pieter Jan't Hoen, Bram Vanschoenwinkel: An Evolutionary Dynamical Analysis of Multi-Agent Learning in Iterated Games. Autonomous Agents and Multi-Agent Systems 12(1): 115-153 (2006)

Steven de Jong, Karl Tuyls, Ida G. Sprinkhuizen-Kuyper: Robust and Scalable Coordination of Potential-Field Driven Agents. CIMCA/IAWTIC 2006: 230

Ben Torben-Nielsen, Karl Tuyls, Eric O. Postma: Shaping Realistic Neuronal Morphologies: An Evolutionary Computation Method. IJCNN 2006: 573-580

Ronald L. Westra, Karl Tuyls, Yvan Saeys, Ann Nowé: Knowledge Discovery and Emergent Complexity in Bioinformatics. KDECB 2006: 1-9

Ben Torben-Nielsen, Karl Tuyls, Eric O. Postma: On the Neuronal Morphology-Function Relationship: A Synthetic Approach. KDECB 2006: 131-144

Ronald L. Westra, Goele Hollanders, Geert Jan Bex, Marc Gyssens, Karl Tuyls: The Identification of Dynamic Gene-Protein Networks. KDECB 2006: 157-170

Geert Jan Bex, Frank Neven, Thomas Schwentick, Karl Tuyls: Inference of Concise DTDs from XML Data. VLDB 2006: 115-126

Karl Tuyls, Pieter Jan't Hoen, Katja Verbeeck, Sandip Sen (Eds.): Learning and Adaption in Multi-Agent Systems, First International Workshop, LAMAS 2005, Utrecht, The Netherlands, July 25, 2005, Revised Selected Papers. Lecture Notes in Computer Science 3898, Springer 2006, isbn 3-540-33053-4

Karl Tuyls, Ann Nowé: Evolutionary game theory and multi-agent reinforcement learning. Knowledge Eng. Review 20(1): 63-90 (2005)

Katja Verbeeck, Ann Nowé, Maarten Peeters, Karl Tuyls: Multi-agent Reinforcement Learning in Stochastic Single and Multi-stage Games. Adaptive Agents and Multi-Agent Systems 2005: 275-294

Katja Verbeeck, Ann Nowé, Karl Tuyls: Coordinated exploration in multi-agent reinforcement learning: an application to load-balancing. AAMAS 2005: 1105-1106

Bart De Vylder, Karl Tuyls: Towards a Common Lexicon in The Naming Game: The Dynamics of Synonymy Reduction. BNAIC 2005: 112-119

Karl Tuyls, Bart Kuijpers: Privacy in Multi-Agent Learning: Securely Inducing a Multi-Agent Decision Tree. EUMAS 2005: 427-438

Pieter Jan't Hoen, Karl Tuyls, Liviu Panait, Sean Luke, Johannes A. La Poutré: An Overview of Cooperative and Competitive Multiagent Learning. LAMAS 2005: 1-46

Tom Croonenborghs, Karl Tuyls, Jan Ramon, Maurice Bruynooghe: Multi-agent Relational Reinforcement Learning. LAMAS 2005: 192-206

Katja Verbeeck, Karl Tuyls, Ann Nowé, Bernard Manderick, Bart Kuijpers (Eds.): BNAIC 2005 - Proceedings of the Seventeenth Belgium-Netherlands Conference on Artificial Intelligence, Brussels, Belgium, October 17-18, 2005. Koninklijke Vlaamse Academie van Belie voor Wetenschappen en Kunsten 2005

Marie Pierre Gleizes, Gal A. Kaminka, Ann Nowé, Sascha Ossowski, Karl Tuyls, Katja Verbeeck (Eds.): EUMAS 2005 - Proceedings of the Third European Workshop on Multi-Agent Systems, Brussels, Belgium, December 7-8, 2005. Koninklijke Vlaamse Academie van Belie voor Wetenschappen en Kunsten 2005

Pieter Jan't Hoen, Karl Tuyls: Analyzing Multi-agent Reinforcement Learning Using Evolutionary Dynamics. ECML 2004: 168-179

Karl Tuyls, Katja Verbeeck, Tom Lenaerts: A selection-mutation model for q-learning in multi-agent systems. AAMAS 2003: 693-700

Karl Tuyls, Katja Verbeeck, Sam Maes: On a Dynamical Analysis of Reinforcement Learning in Games: Emergence of Occam's Razor. CEEMAS 2003: 335-344

Karl Tuyls, Dries Heytens, Ann Nowé, Bernard Manderick: Extended Replicator Dynamics as a Key to Reinforcement Learning in Multi-agent Systems. ECML 2003: 421-431

Karl Tuyls, Sam Maes, Bernard Manderick: Q-Learning in Simulated Robotic Soccer - Large State Spaces and Incomplete Information. ICMLA 2002: 226-232

Karl Tuyls, Sam Maes, Bernard Manderick: Reinforcement Learning in Large State Spaces. RoboCup 2002: 319-326