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Karl Tuyls
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- affiliation: Google DeepMind
- affiliation: University of Liverpool
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2020 – today
- 2024
- [j45]Mark Rowland, Rémi Munos, Mohammad Gheshlaghi Azar, Yunhao Tang, Georg Ostrovski, Anna Harutyunyan, Karl Tuyls, Marc G. Bellemare, Will Dabney:
An Analysis of Quantile Temporal-Difference Learning. J. Mach. Learn. Res. 25: 163:1-163:47 (2024) - [c148]Yunfan Zhao, Nikhil Behari, Edward Hughes, Edwin Zhang, Dheeraj Nagaraj, Karl Tuyls, Aparna Taneja, Milind Tambe:
Towards Zero Shot Learning in Restless Multi-armed Bandits. AAMAS 2024: 2618-2620 - [c147]Yunfan Zhao, Nikhil Behari, Edward Hughes, Edwin Zhang, Dheeraj Nagaraj, Karl Tuyls, Aparna Taneja, Milind Tambe:
Towards a Pretrained Model for Restless Bandits via Multi-arm Generalization. IJCAI 2024: 321-329 - [i58]Ian Gemp, Yoram Bachrach, Marc Lanctot, Roma Patel, Vibhavari Dasagi, Luke Marris, Georgios Piliouras, Siqi Liu, Karl Tuyls:
States as Strings as Strategies: Steering Language Models with Game-Theoretic Solvers. CoRR abs/2402.01704 (2024) - [i57]Michael P. Wellman
, Karl Tuyls, Amy Greenwald
Empirical Game-Theoretic Analysis: A Survey. CoRR abs/2403.04018 (2024) - [i56]Raphael Koster, Miruna Pîslar, Andrea Tacchetti, Jan Balaguer, Leqi Liu, Romuald Elie, Oliver P. Hauser, Karl Tuyls, Matt M. Botvinick, Christopher Summerfield:
Using deep reinforcement learning to promote sustainable human behaviour on a common pool resource problem. CoRR abs/2404.15059 (2024) - 2023
- [c146]Karl Tuyls:
Multiagent Learning: From Fundamentals to Foundation Models. AAMAS 2023: 1 - [c145]Jakob Bauer, Kate Baumli, Feryal M. P. Behbahani, Avishkar Bhoopchand, Nathalie Bradley-Schmieg, Michael Chang, Natalie Clay, Adrian Collister, Vibhavari Dasagi, Lucy Gonzalez, Karol Gregor, Edward Hughes, Sheleem Kashem, Maria Loks-Thompson, Hannah Openshaw, Jack Parker-Holder, Shreya Pathak, Nicolas Perez Nieves, Nemanja Rakicevic, Tim Rocktäschel, Yannick Schroecker, Satinder Singh, Jakub Sygnowski, Karl Tuyls, Sarah York, Alexander Zacherl, Lei M. Zhang:
Human-Timescale Adaptation in an Open-Ended Task Space. ICML 2023: 1887-1935 - [i55]Mark Rowland, Rémi Munos, Mohammad Gheshlaghi Azar, Yunhao Tang, Georg Ostrovski, Anna Harutyunyan, Karl Tuyls, Marc G. Bellemare, Will Dabney:
An Analysis of Quantile Temporal-Difference Learning. CoRR abs/2301.04462 (2023) - [i54]Adaptive Agent Team, Jakob Bauer, Kate Baumli, Satinder Baveja, Feryal M. P. Behbahani, Avishkar Bhoopchand, Nathalie Bradley-Schmieg, Michael Chang, Natalie Clay, Adrian Collister, Vibhavari Dasagi, Lucy Gonzalez, Karol Gregor, Edward Hughes, Sheleem Kashem, Maria Loks-Thompson, Hannah Openshaw, Jack Parker-Holder, Shreya Pathak, Nicolas Perez Nieves, Nemanja Rakicevic, Tim Rocktäschel, Yannick Schroecker, Jakub Sygnowski, Karl Tuyls, Sarah York, Alexander Zacherl, Lei Zhang:
Human-Timescale Adaptation in an Open-Ended Task Space. CoRR abs/2301.07608 (2023) - [i53]Udari Madhushani, Kevin R. McKee, John P. Agapiou, Joel Z. Leibo, Richard Everett, Thomas W. Anthony, Edward Hughes, Karl Tuyls, Edgar A. Duéñez-Guzmán
Heterogeneous Social Value Orientation Leads to Meaningful Diversity in Sequential Social Dilemmas. CoRR abs/2305.00768 (2023) - [i52]Zhe Wang, Petar Velickovic, Daniel Hennes, Nenad Tomasev, Laurel Prince, Michael Kaisers, Yoram Bachrach, Romuald Elie, Li Kevin Wenliang, Federico Piccinini, William Spearman, Ian Graham, Jerome T. Connor, Yi Yang, Adrià Recasens, Mina Khan, Nathalie Beauguerlange, Pablo Sprechmann, Pol Moreno, Nicolas Heess, Michael Bowling, Demis Hassabis, Karl Tuyls:
TacticAI: an AI assistant for football tactics. CoRR abs/2310.10553 (2023) - [i51]Yunfan Zhao, Nikhil Behari, Edward Hughes, Edwin Zhang, Dheeraj Nagaraj, Karl Tuyls, Aparna Taneja, Milind Tambe:
Towards Zero Shot Learning in Restless Multi-armed Bandits. CoRR abs/2310.14526 (2023) - 2022
- [j44]Ian Gemp, Thomas W. Anthony, Yoram Bachrach, Avishkar Bhoopchand, Kalesha Bullard, Jerome T. Connor, Vibhavari Dasagi, Bart De Vylder, Edgar A. Duéñez-Guzmán
Developing, evaluating and scaling learning agents in multi-agent environments. AI Commun. 35(4): 271-284 (2022) - [j43]Georgios Piliouras, Mark Rowland, Shayegan Omidshafiei, Romuald Elie, Daniel Hennes, Jerome T. Connor, Karl Tuyls:
Evolutionary Dynamics and Phi-Regret Minimization in Games. J. Artif. Intell. Res. 74: 1125-1158 (2022) - [j42]Siqi Liu
From motor control to team play in simulated humanoid football. Sci. Robotics 7(69) (2022) - [c144]Paul Muller, Mark Rowland, Romuald Elie, Georgios Piliouras, Julien Pérolat, Mathieu Laurière, Raphaël Marinier, Olivier Pietquin, Karl Tuyls:
Learning Equilibria in Mean-Field Games: Introducing Mean-Field PSRO. AAMAS 2022: 926-934 - [c143]Julien Pérolat, Sarah Perrin, Romuald Elie, Mathieu Laurière, Georgios Piliouras, Matthieu Geist, Karl Tuyls, Olivier Pietquin:
Scaling Mean Field Games by Online Mirror Descent. AAMAS 2022: 1028-1037 - [c142]Luke Marris, Ian Gemp, Thomas Anthony, Andrea Tacchetti, Siqi Liu, Karl Tuyls:
Turbocharging Solution Concepts: Solving NEs, CEs and CCEs with Neural Equilibrium Solvers. NeurIPS 2022 - [c141]James Butterworth
Generative Models over Neural Controllers for Transfer Learning. PPSN (1) 2022: 400-413 - [d2]Siqi Liu
Figure Data for the paper "From Motor Control to Team Play in Simulated Humanoid Football". Zenodo, 2022 - [d1]Julien Pérolat
Figure Data for the paper "Mastering the Game of Stratego with Model-Free Multiagent Reinforcement Learning". Zenodo, 2022 - [i50]Julien Pérolat, Bart De Vylder, Daniel Hennes, Eugene Tarassov, Florian Strub, Vincent de Boer, Paul Muller, Jerome T. Connor, Neil Burch, Thomas W. Anthony, Stephen McAleer, Romuald Elie, Sarah H. Cen, Zhe Wang, Audrunas Gruslys, Aleksandra Malysheva, Mina Khan, Sherjil Ozair, Finbarr Timbers, Toby Pohlen, Tom Eccles, Mark Rowland, Marc Lanctot, Jean-Baptiste Lespiau, Bilal Piot, Shayegan Omidshafiei, Edward Lockhart, Laurent Sifre, Nathalie Beauguerlange, Rémi Munos, David Silver, Satinder Singh, Demis Hassabis, Karl Tuyls:
Mastering the Game of Stratego with Model-Free Multiagent Reinforcement Learning. CoRR abs/2206.15378 (2022) - [i49]Paul Muller, Romuald Elie, Mark Rowland, Mathieu Laurière, Julien Pérolat, Sarah Perrin, Matthieu Geist, Georgios Piliouras, Olivier Pietquin, Karl Tuyls:
Learning Correlated Equilibria in Mean-Field Games. CoRR abs/2208.10138 (2022) - [i48]Ian Gemp, Thomas W. Anthony, Yoram Bachrach, Avishkar Bhoopchand, Kalesha Bullard, Jerome T. Connor, Vibhavari Dasagi, Bart De Vylder, Edgar A. Duéñez-Guzmán, Romuald Elie, Richard Everett, Daniel Hennes, Edward Hughes, Mina Khan, Marc Lanctot, Kate Larson
Developing, Evaluating and Scaling Learning Agents in Multi-Agent Environments. CoRR abs/2209.10958 (2022) - [i47]Luke Marris, Marc Lanctot, Ian Gemp, Shayegan Omidshafiei, Stephen McAleer, Jerome T. Connor, Karl Tuyls, Thore Graepel:
Game Theoretic Rating in N-player general-sum games with Equilibria. CoRR abs/2210.02205 (2022) - [i46]Luke Marris, Ian Gemp, Thomas W. Anthony, Andrea Tacchetti, Siqi Liu, Karl Tuyls:
Turbocharging Solution Concepts: Solving NEs, CEs and CCEs with Neural Equilibrium Solvers. CoRR abs/2210.09257 (2022) - 2021
- [j41]Karl Tuyls, Shayegan Omidshafiei, Paul Muller, Zhe Wang, Jerome T. Connor, Daniel Hennes, Ian Graham, William Spearman, Tim Waskett, Dafydd Steele, Pauline Luc, Adrià Recasens, Alexandre Galashov, Gregory Thornton, Romuald Elie, Pablo Sprechmann, Pol Moreno, Kris Cao, Marta Garnelo, Praneet Dutta, Michal Valko, Nicolas Heess, Alex Bridgland, Julien Pérolat, Bart De Vylder, S. M. Ali Eslami, Mark Rowland, Andrew Jaegle, Rémi Munos, Trevor Back, Razia Ahamed, Simon Bouton, Nathalie Beauguerlange, Jackson Broshear, Thore Graepel, Demis Hassabis:
Game Plan: What AI can do for Football, and What Football can do for AI. J. Artif. Intell. Res. 71: 41-88 (2021) - [c140]Luke Marris, Paul Muller, Marc Lanctot, Karl Tuyls, Thore Graepel:
Multi-Agent Training beyond Zero-Sum with Correlated Equilibrium Meta-Solvers. ICML 2021: 7480-7491 - [c139]Julien Pérolat, Rémi Munos, Jean-Baptiste Lespiau, Shayegan Omidshafiei, Mark Rowland, Pedro A. Ortega, Neil Burch, Thomas W. Anthony, David Balduzzi, Bart De Vylder, Georgios Piliouras, Marc Lanctot, Karl Tuyls:
From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization. ICML 2021: 8525-8535 - [i45]Julien Pérolat, Sarah Perrin, Romuald Elie, Mathieu Laurière, Georgios Piliouras, Matthieu Geist, Karl Tuyls, Olivier Pietquin:
Scaling up Mean Field Games with Online Mirror Descent. CoRR abs/2103.00623 (2021) - [i44]Siqi Liu, Guy Lever, Zhe Wang, Josh Merel, S. M. Ali Eslami, Daniel Hennes, Wojciech M. Czarnecki, Yuval Tassa, Shayegan Omidshafiei, Abbas Abdolmaleki, Noah Y. Siegel, Leonard Hasenclever, Luke Marris, Saran Tunyasuvunakool, H. Francis Song, Markus Wulfmeier, Paul Muller, Tuomas Haarnoja, Brendan D. Tracey, Karl Tuyls, Thore Graepel, Nicolas Heess:
From Motor Control to Team Play in Simulated Humanoid Football. CoRR abs/2105.12196 (2021) - [i43]Shayegan Omidshafiei, Daniel Hennes, Marta Garnelo, Eugene Tarassov, Zhe Wang, Romuald Elie, Jerome T. Connor, Paul Muller, Ian Graham, William Spearman, Karl Tuyls:
Time-series Imputation of Temporally-occluded Multiagent Trajectories. CoRR abs/2106.04219 (2021) - [i42]Luke Marris, Paul Muller, Marc Lanctot, Karl Tuyls, Thore Graepel:
Multi-Agent Training beyond Zero-Sum with Correlated Equilibrium Meta-Solvers. CoRR abs/2106.09435 (2021) - [i41]Georgios Piliouras, Mark Rowland, Shayegan Omidshafiei, Romuald Elie, Daniel Hennes, Jerome T. Connor, Karl Tuyls:
Evolutionary Dynamics and Φ-Regret Minimization in Games. CoRR abs/2106.14668 (2021) - [i40]Edgar A. Duéñez-Guzmán, Kevin R. McKee, Yiran Mao, Ben Coppin, Silvia Chiappa, Alexander Sasha Vezhnevets, Michiel A. Bakker, Yoram Bachrach, Suzanne Sadedin, William Isaac, Karl Tuyls, Joel Z. Leibo:
Statistical discrimination in learning agents. CoRR abs/2110.11404 (2021) - [i39]Paul Muller, Mark Rowland, Romuald Elie, Georgios Piliouras, Julien Pérolat, Mathieu Laurière, Raphaël Marinier, Olivier Pietquin, Karl Tuyls:
Learning Equilibria in Mean-Field Games: Introducing Mean-Field PSRO. CoRR abs/2111.08350 (2021) - 2020
- [j40]Karl Tuyls
Bounds and dynamics for empirical game theoretic analysis. Auton. Agents Multi Agent Syst. 34(1): 7 (2020) - [c138]Daniel Hennes, Dustin Morrill, Shayegan Omidshafiei, Rémi Munos, Julien Pérolat, Marc Lanctot, Audrunas Gruslys, Jean-Baptiste Lespiau, Paavo Parmas, Edgar A. Duéñez-Guzmán, Karl Tuyls:
Neural Replicator Dynamics: Multiagent Learning via Hedging Policy Gradients. AAMAS 2020: 492-501 - [c137]Gregory Palmer, Benjamin Schnieders, Rahul Savani
The Automated Inspection of Opaque Liquid Vaccines. ECAI 2020: 1898-1905 - [c136]Paul Muller, Shayegan Omidshafiei, Mark Rowland, Karl Tuyls, Julien Pérolat, Siqi Liu, Daniel Hennes, Luke Marris, Marc Lanctot, Edward Hughes, Zhe Wang, Guy Lever, Nicolas Heess, Thore Graepel, Rémi Munos:
A Generalized Training Approach for Multiagent Learning. ICLR 2020 - [c135]Rémi Munos, Julien Pérolat, Jean-Baptiste Lespiau, Mark Rowland, Bart De Vylder, Marc Lanctot, Finbarr Timbers, Daniel Hennes, Shayegan Omidshafiei, Audrunas Gruslys, Mohammad Gheshlaghi Azar, Edward Lockhart, Karl Tuyls:
Fast computation of Nash Equilibria in Imperfect Information Games. ICML 2020: 7119-7129 - [c134]Wojciech M. Czarnecki, Gauthier Gidel, Brendan D. Tracey, Karl Tuyls, Shayegan Omidshafiei, David Balduzzi, Max Jaderberg:
Real World Games Look Like Spinning Tops. NeurIPS 2020 - [i38]Julien Pérolat, Rémi Munos, Jean-Baptiste Lespiau, Shayegan Omidshafiei, Mark Rowland, Pedro A. Ortega, Neil Burch, Thomas W. Anthony, David Balduzzi, Bart De Vylder, Georgios Piliouras, Marc Lanctot, Karl Tuyls:
From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization. CoRR abs/2002.08456 (2020) - [i37]Gregory Palmer, Benjamin Schnieders, Rahul Savani
The Automated Inspection of Opaque Liquid Vaccines. CoRR abs/2002.09406 (2020) - [i36]Wojciech Marian Czarnecki, Gauthier Gidel, Brendan D. Tracey, Karl Tuyls, Shayegan Omidshafiei, David Balduzzi, Max Jaderberg:
Real World Games Look Like Spinning Tops. CoRR abs/2004.09468 (2020) - [i35]Shayegan Omidshafiei, Karl Tuyls, Wojciech M. Czarnecki, Francisco C. Santos, Mark Rowland, Jerome T. Connor, Daniel Hennes, Paul Muller, Julien Pérolat, Bart De Vylder, Audrunas Gruslys, Rémi Munos:
Navigating the Landscape of Games. CoRR abs/2005.01642 (2020) - [i34]Audrunas Gruslys, Marc Lanctot, Rémi Munos, Finbarr Timbers, Martin Schmid, Julien Pérolat, Dustin Morrill, Vinícius Flores Zambaldi, Jean-Baptiste Lespiau, John Schultz, Mohammad Gheshlaghi Azar, Michael Bowling, Karl Tuyls:
The Advantage Regret-Matching Actor-Critic. CoRR abs/2008.12234 (2020) - [i33]Karl Tuyls, Shayegan Omidshafiei, Paul Muller, Zhe Wang, Jerome T. Connor, Daniel Hennes, Ian Graham, William Spearman, Tim Waskett, Dafydd Steele, Pauline Luc, Adrià Recasens, Alexandre Galashov, Gregory Thornton, Romuald Elie, Pablo Sprechmann, Pol Moreno, Kris Cao, Marta Garnelo, Praneet Dutta, Michal Valko, Nicolas Heess, Alex Bridgland, Julien Pérolat, Bart De Vylder, S. M. Ali Eslami, Mark Rowland, Andrew Jaegle, Rémi Munos, Trevor Back, Razia Ahamed, Simon Bouton, Nathalie Beauguerlange, Jackson Broshear, Thore Graepel, Demis Hassabis:
Game Plan: What AI can do for Football, and What Football can do for AI. CoRR abs/2011.09192 (2020)
2010 – 2019
- 2019
- [j39]Chengwei Zhang
SA-IGA: a multiagent reinforcement learning method towards socially optimal outcomes. Auton. Agents Multi Agent Syst. 33(4): 403-429 (2019) - [j38]Bijan Ranjbar Sahraei, Hossein Rahmani, Gerhard Weiss, Karl Tuyls:
Distant supervision of relation extraction in sparse data. Intell. Data Anal. 23(5): 1145-1166 (2019) - [j37]Alistair Letcher, David Balduzzi, Sébastien Racanière, James Martens, Jakob N. Foerster, Karl Tuyls, Thore Graepel:
Differentiable Game Mechanics. J. Mach. Learn. Res. 20: 84:1-84:40 (2019) - [j36]Kimberly N. McGuire
A comparative study of bug algorithms for robot navigation. Robotics Auton. Syst. 121 (2019) - [j35]Kimberly McGuire
Minimal navigation solution for a swarm of tiny flying robots to explore an unknown environment. Sci. Robotics 4(35) (2019) - [c133]Gregory Palmer, Rahul Savani, Karl Tuyls:
Negative Update Intervals in Deep Multi-Agent Reinforcement Learning. AAMAS 2019: 43-51 - [c132]Richard Klíma, Daan Bloembergen, Michael Kaisers, Karl Tuyls:
Robust Temporal Difference Learning for Critical Domains. AAMAS 2019: 350-358 - [c131]Benjamin Schnieders, Shan Luo, Gregory Palmer, Karl Tuyls:
Fully Convolutional One-Shot Object Segmentation for Industrial Robotics. AAMAS 2019: 1161-1169 - [c130]Joe Collenette, Katie Atkinson, Daan Bloembergen, Karl Tuyls:
Stability of Human-Inspired Agent Societies. AAMAS 2019: 1889-1891 - [c129]James Butterworth
Evolving indoor navigational strategies using gated recurrent units in NEAT. GECCO (Companion) 2019: 111-112 - [c128]Vinícius Flores Zambaldi, David Raposo, Adam Santoro, Victor Bapst, Yujia Li, Igor Babuschkin, Karl Tuyls, David P. Reichert, Timothy P. Lillicrap, Edward Lockhart, Murray Shanahan, Victoria Langston, Razvan Pascanu, Matthew M. Botvinick, Oriol Vinyals, Peter W. Battaglia:
Deep reinforcement learning with relational inductive biases. ICLR (Poster) 2019 - [c127]Edward Lockhart, Marc Lanctot, Julien Pérolat, Jean-Baptiste Lespiau, Dustin Morrill, Finbarr Timbers, Karl Tuyls:
Computing Approximate Equilibria in Sequential Adversarial Games by Exploitability Descent. IJCAI 2019: 464-470 - [c126]Joe Collenette, Katie Atkinson, Daan Bloembergen, Karl Tuyls:
Stability of Cooperation in Societies of Emotional and Moody Agents. ALIFE 2019: 467-474 - [c125]Mark Rowland, Shayegan Omidshafiei, Karl Tuyls, Julien Pérolat, Michal Valko, Georgios Piliouras, Rémi Munos:
Multiagent Evaluation under Incomplete Information. NeurIPS 2019: 12270-12282 - [i32]Richard Klíma, Daan Bloembergen, Michael Kaisers, Karl Tuyls:
Robust temporal difference learning for critical domains. CoRR abs/1901.08021 (2019) - [i31]Benjamin Schnieders, Shan Luo, Gregory Palmer, Karl Tuyls:
Fully Convolutional One-Shot Object Segmentation for Industrial Robotics. CoRR abs/1903.00683 (2019) - [i30]Shayegan Omidshafiei, Christos H. Papadimitriou, Georgios Piliouras, Karl Tuyls, Mark Rowland, Jean-Baptiste Lespiau, Wojciech M. Czarnecki, Marc Lanctot, Julien Pérolat, Rémi Munos:
α-Rank: Multi-Agent Evaluation by Evolution. CoRR abs/1903.01373 (2019) - [i29]Edward Lockhart, Marc Lanctot, Julien Pérolat, Jean-Baptiste Lespiau, Dustin Morrill, Finbarr Timbers, Karl Tuyls:
Computing Approximate Equilibria in Sequential Adversarial Games by Exploitability Descent. CoRR abs/1903.05614 (2019) - [i28]James Butterworth, Rahul Savani
Evolving Indoor Navigational Strategies Using Gated Recurrent Units In NEAT. CoRR abs/1904.06239 (2019) - [i27]Alistair Letcher, David Balduzzi, Sébastien Racanière, James Martens, Jakob N. Foerster, Karl Tuyls, Thore Graepel:
Differentiable Game Mechanics. CoRR abs/1905.04926 (2019) - [i26]Shayegan Omidshafiei, Daniel Hennes, Dustin Morrill, Rémi Munos, Julien Pérolat, Marc Lanctot, Audrunas Gruslys, Jean-Baptiste Lespiau, Karl Tuyls:
Neural Replicator Dynamics. CoRR abs/1906.00190 (2019) - [i25]Marc Lanctot, Edward Lockhart, Jean-Baptiste Lespiau, Vinícius Flores Zambaldi, Satyaki Upadhyay, Julien Pérolat, Sriram Srinivasan, Finbarr Timbers, Karl Tuyls, Shayegan Omidshafiei, Daniel Hennes, Dustin Morrill, Paul Muller, Timo Ewalds
OpenSpiel: A Framework for Reinforcement Learning in Games. CoRR abs/1908.09453 (2019) - [i24]Mark Rowland, Shayegan Omidshafiei, Karl Tuyls, Julien Pérolat, Michal Valko, Georgios Piliouras, Rémi Munos:
Multiagent Evaluation under Incomplete Information. CoRR abs/1909.09849 (2019) - [i23]Paul Muller, Shayegan Omidshafiei, Mark Rowland, Karl Tuyls, Julien Pérolat, Siqi Liu, Daniel Hennes, Luke Marris, Marc Lanctot, Edward Hughes, Zhe Wang, Guy Lever, Nicolas Heess, Thore Graepel, Rémi Munos:
A Generalized Training Approach for Multiagent Learning. CoRR abs/1909.12823 (2019) - 2018
- [j34]Christopher Amato
Reports on the 2018 AAAI Spring Symposium Series. AI Mag. 39(4): 29-35 (2018) - [j33]Daniel Claes
Multi robot collision avoidance in a shared workspace. Auton. Robots 42(8): 1749-1770 (2018) - [j32]Richard Klíma, Daan Bloembergen, Rahul Savani
Space Debris Removal: Learning to Cooperate and the Price of Anarchy. Frontiers Robotics AI 5: 54 (2018) - [j31]Tim de Bruin, Jens Kober, Karl Tuyls, Robert Babuska:
Experience Selection in Deep Reinforcement Learning for Control. J. Mach. Learn. Res. 19: 9:1-9:56 (2018) - [j30]Tim de Bruin
Integrating State Representation Learning Into Deep Reinforcement Learning. IEEE Robotics Autom. Lett. 3(2): 1394-1401 (2018) - [c124]Richard Klíma, Karl Tuyls, Frans A. Oliehoek:
Model-Based Reinforcement Learning under Periodical Observability. AAAI Spring Symposia 2018 - [c123]Karl Tuyls, Julien Pérolat, Marc Lanctot, Joel Z. Leibo, Thore Graepel:
A Generalised Method for Empirical Game Theoretic Analysis. AAMAS 2018: 77-85 - [c122]Gregory Palmer, Karl Tuyls, Daan Bloembergen, Rahul Savani:
Lenient Multi-Agent Deep Reinforcement Learning. AAMAS 2018: 443-451 - [c121]James Butterworth, Bastian Broecker, Karl Tuyls, Paolo Paoletti:
Evolving Coverage Behaviours For MAVs Using NEAT. AAMAS 2018: 1886-1888 - [c120]Peter Sunehag, Guy Lever, Audrunas Gruslys, Wojciech Marian Czarnecki, Vinícius Flores Zambaldi, Max Jaderberg, Marc Lanctot, Nicolas Sonnerat, Joel Z. Leibo, Karl Tuyls, Thore Graepel:
Value-Decomposition Networks For Cooperative Multi-Agent Learning Based On Team Reward. AAMAS 2018: 2085-2087 - [c119]Chengwei Zhang, Xiaohong Li, Jianye Hao, Siqi Chen, Karl Tuyls, Zhiyong Feng:
SCC-rFMQ Learning in Cooperative Markov Games with Continuous Actions. AAMAS 2018: 2162-2164 - [c118]Kris Cao, Angeliki Lazaridou, Marc Lanctot, Joel Z. Leibo, Karl Tuyls, Stephen Clark:
Emergent Communication through Negotiation. ICLR (Poster) 2018 - [c117]Angeliki Lazaridou, Karl Moritz Hermann, Karl Tuyls, Stephen Clark:
Emergence of Linguistic Communication from Referential Games with Symbolic and Pixel Input. ICLR 2018 - [c116]David Balduzzi, Sébastien Racanière, James Martens, Jakob N. Foerster, Karl Tuyls, Thore Graepel:
The Mechanics of n-Player Differentiable Games. ICML 2018: 363-372 - [c115]Bastian Broecker, Karl Tuyls, James Butterworth
Distance-Based Multi-Robot Coordination on Pocket Drones. ICRA 2018: 6389-6394 - [c114]Benjamin Schnieders, Karl Tuyls:
Fast Convergence for Object Detection by Learning how to Combine Error Functions. IROS 2018: 7329-7335 - [c113]Joe Collenette, Katie Atkinson, Daan Bloembergen, Karl Tuyls:
On the Role of Mobility and Interaction Topologies in Social Dilemmas. ALIFE 2018: 477-484 - [c112]David Balduzzi, Karl Tuyls, Julien Pérolat, Thore Graepel:
Re-evaluating evaluation. NeurIPS 2018: 3272-3283 - [c111]Edward Hughes, Joel Z. Leibo, Matthew Phillips, Karl Tuyls, Edgar A. Duéñez-Guzmán, Antonio García Castañeda, Iain Dunning, Tina Zhu, Kevin R. McKee, Raphael Koster, Heather Roff, Thore Graepel:
Inequity aversion improves cooperation in intertemporal social dilemmas. NeurIPS 2018: 3330-3340 - [c110]Sriram Srinivasan, Marc Lanctot, Vinícius Flores Zambaldi, Julien Pérolat, Karl Tuyls, Rémi Munos, Michael Bowling:
Actor-Critic Policy Optimization in Partially Observable Multiagent Environments. NeurIPS 2018: 3426-3439 - [i22]David Balduzzi, Sébastien Racanière, James Martens, Jakob N. Foerster, Karl Tuyls, Thore Graepel:
The Mechanics of n-Player Differentiable Games. CoRR abs/1802.05642 (2018) - [i21]Chengwei Zhang, Xiaohong Li, Jianye Hao, Siqi Chen, Karl Tuyls, Wanli Xue:
SA-IGA: A Multiagent Reinforcement Learning Method Towards Socially Optimal Outcomes. CoRR abs/1803.03021 (2018) - [i20]Karl Tuyls, Julien Pérolat, Marc Lanctot, Joel Z. Leibo, Thore Graepel:
A Generalised Method for Empirical Game Theoretic Analysis. CoRR abs/1803.06376 (2018) - [i19]Edward Hughes, Joel Z. Leibo, Matthew G. Philips, Karl Tuyls, Edgar A. Duéñez-Guzmán, Antonio García Castañeda, Iain Dunning, Tina Zhu, Kevin R. McKee, Raphael Koster, Heather Roff, Thore Graepel:
Inequity aversion resolves intertemporal social dilemmas. CoRR abs/1803.08884 (2018) - [i18]Kris Cao, Angeliki Lazaridou, Marc Lanctot, Joel Z. Leibo, Karl Tuyls, Stephen Clark:
Emergent Communication through Negotiation. CoRR abs/1804.03980 (2018) - [i17]Angeliki Lazaridou, Karl Moritz Hermann, Karl Tuyls, Stephen Clark:
Emergence of Linguistic Communication from Referential Games with Symbolic and Pixel Input. CoRR abs/1804.03984 (2018) - [i16]Vinícius Flores Zambaldi, David Raposo, Adam Santoro, Victor Bapst, Yujia Li, Igor Babuschkin, Karl Tuyls, David P. Reichert, Timothy P. Lillicrap, Edward Lockhart, Murray Shanahan, Victoria Langston, Razvan Pascanu, Matthew M. Botvinick, Oriol Vinyals, Peter W. Battaglia:
Relational Deep Reinforcement Learning. CoRR abs/1806.01830 (2018) - [i15]David Balduzzi, Karl Tuyls, Julien Pérolat, Thore Graepel:
Re-evaluating evaluation. CoRR abs/1806.02643 (2018) - [i14]Benjamin Schnieders, Karl Tuyls:
Fast Convergence for Object Detection by Learning how to Combine Error Functions. CoRR abs/1808.04480 (2018) - [i13]Kimberly McGuire, Guido de Croon, Karl Tuyls:
A Comparative Study of Bug Algorithms for Robot Navigation. CoRR abs/1808.05050 (2018) - [i12]Gregory Palmer, Rahul Savani
Negative Update Intervals in Deep Multi-Agent Reinforcement Learning. CoRR abs/1809.05096 (2018) - [i11]Chengwei Zhang, Xiaohong Li, Jianye Hao, Siqi Chen, Karl Tuyls, Zhiyong Feng, Wanli Xue, Rong Chen:
SCC-rFMQ Learning in Cooperative Markov Games with Continuous Actions. CoRR abs/1809.06625 (2018) - [i10]Sriram Srinivasan, Marc Lanctot, Vinícius Flores Zambaldi, Julien Pérolat, Karl Tuyls, Rémi Munos, Michael Bowling:
Actor-Critic Policy Optimization in Partially Observable Multiagent Environments. CoRR abs/1810.09026 (2018) - 2017
- [j29]Joe Collenette, Katie Atkinson, Daan Bloembergen
Environmental effects on simulated emotional and moody agents. Knowl. Eng. Rev. 32: e19 (2017) - [j28]Kimberly McGuire, Guido de Croon, Christophe De Wagter
Efficient Optical Flow and Stereo Vision for Velocity Estimation and Obstacle Avoidance on an Autonomous Pocket Drone. IEEE Robotics Autom. Lett. 2(2): 1070-1076 (2017) - [c109]Daniel Claes, Frans A. Oliehoek, Hendrik Baier, Karl Tuyls:
Decentralised Online Planning for Multi-Robot Warehouse Commissioning. AAMAS 2017: 492-500 - [c108]Joe Collenette, Katie Atkinson, Daan Bloembergen
Mood modelling within reinforcement learning. ECAL 2017: 106-113 - [c107]Karl Tuyls, Peter Stone:
Multiagent Learning Paradigms. EUMAS/AT 2017: 3-21 - [c106]Joscha-David Fossel, Karl Tuyls
NOctoSLAM: Fast octree surface normal mapping and registration. IROS 2017: 6764-6769 - [c105]Julien Pérolat, Joel Z. Leibo, Vinícius Flores Zambaldi, Charles Beattie, Karl Tuyls, Thore Graepel:
A multi-agent reinforcement learning model of common-pool resource appropriation. NIPS 2017: 3643-3652 - [c104]Marc Lanctot, Vinícius Flores Zambaldi, Audrunas Gruslys, Angeliki Lazaridou, Karl Tuyls, Julien Pérolat, David Silver, Thore Graepel:
A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning. NIPS 2017: 4190-4203 - [i9]Peter Sunehag, Guy Lever, Audrunas Gruslys, Wojciech Marian Czarnecki, Vinícius Flores Zambaldi, Max Jaderberg, Marc Lanctot, Nicolas Sonnerat, Joel Z. Leibo, Karl Tuyls, Thore Graepel:
Value-Decomposition Networks For Cooperative Multi-Agent Learning. CoRR abs/1706.05296 (2017) - [i8]Gregory Palmer, Karl Tuyls, Daan Bloembergen, Rahul Savani
Lenient Multi-Agent Deep Reinforcement Learning. CoRR abs/1707.04402 (2017) - [i7]Julien Pérolat, Joel Z. Leibo, Vinícius Flores Zambaldi, Charles Beattie, Karl Tuyls, Thore Graepel:
A multi-agent reinforcement learning model of common-pool resource appropriation. CoRR abs/1707.06600 (2017) - [i6]Marc Lanctot, Vinícius Flores Zambaldi, Audrunas Gruslys, Angeliki Lazaridou, Karl Tuyls, Julien Pérolat, David Silver, Thore Graepel:
A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning. CoRR abs/1711.00832 (2017) - [i5]Karl Tuyls, Julien Pérolat, Marc Lanctot, Georg Ostrovski, Rahul Savani
Symmetric Decomposition of Asymmetric Games. CoRR abs/1711.05074 (2017) - 2016
- [j27]Richard Klíma, Daan Bloembergen
Space Debris Removal: A Game Theoretic Analysis. Games 7(3): 20 (2016) - [j26]Hossein Rahmani
Entity resolution in disjoint graphs: An application on genealogical data. Intell. Data Anal. 20(2): 455-475 (2016) - [j25]Bijan Ranjbar Sahraei
On the prevalence of hierarchies in social networks. Soc. Netw. Anal. Min. 6(1): 58:1-58:16 (2016) - [c103]Daan Bloembergen
A Telepresence-Robot Approach for Efficient Coordination of Swarms. ALIFE 2016: 666-673 - [c102]Joe Collenette, Katie Atkinson, Daan Bloembergen, Karl Tuyls
Modelling Mood in Co-operative Emotional Agents. DARS 2016: 559-572 - [c101]Xiaohong Li, Chengwei Zhang, Jianye Hao, Karl Tuyls
Socially-Aware Multiagent Learning: Towards Socially Optimal Outcomes. ECAI 2016: 533-541 - [c100]Richard Klíma, Daan Bloembergen, Rahul Savani
Space Debris Removal: A Game Theoretic Analysis. ECAI 2016: 1658-1659 - [c99]Rik Claessens, Alta de Waal, Johan Pieter de Villiers, Ate Penders, Gregor Pavlin, Karl Tuyls
Bayesian Inference in Dynamic Domains using Logical OR Gates. ICEIS (2) 2016: 134-142 - [c98]Kimberly McGuire, Guido C. H. E. de Croon, Christophe De Wagter
Local histogram matching for efficient optical flow computation applied to velocity estimation on pocket drones. ICRA 2016: 3255-3260 - [c97]Tim de Bruin, Jens Kober
Improved deep reinforcement learning for robotics through distribution-based experience retention. IROS 2016: 3947-3952 - [c96]Joe Collenette, Katie Atkinson, Daan Bloembergen, Karl Tuyls
The Effect of Mobility and Emotion on Interactions in Multi-Agent Systems. STAIRS 2016: 39-50 - [e9]Catholijn M. Jonker, Stacy Marsella, John Thangarajah, Karl Tuyls:
Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems, Singapore, May 9-13, 2016. ACM 2016, ISBN 978-1-4503-4239-1 [contents] - [i4]Kimberly McGuire, Guido C. H. E. de Croon, Christophe De Wagter, Bart Remes, Karl Tuyls, Hilbert J. Kappen:
Local Histogram Matching for Efficient Optical Flow Computation Applied to Velocity Estimation on Pocket Drones. CoRR abs/1603.07644 (2016) - [i3]Kimberly McGuire, Guido de Croon, Christophe De Wagter, Karl Tuyls, Hilbert J. Kappen:
Efficient Optical flow and Stereo Vision for Velocity Estimation and Obstacle Avoidance on an Autonomous Pocket Drone. CoRR abs/1612.06702 (2016) - 2015
- [j24]Daan Bloembergen
Trading in markets with noisy information: an evolutionary analysis. Connect. Sci. 27(3): 253-268 (2015) - [j23]Daan Bloembergen, Karl Tuyls
Evolutionary Dynamics of Multi-Agent Learning: A Survey. J. Artif. Intell. Res. 53: 659-697 (2015) - [j22]Decebal Constantin Mocanu
Factored four way conditional restricted Boltzmann machines for activity recognition. Pattern Recognit. Lett. 66: 100-108 (2015) - [j21]Daniel Hennes
Metastrategies in Large-Scale Bargaining Settings. ACM Trans. Intell. Syst. Technol. 7(1): 10:1-10:23 (2015) - [c95]Bijan Ranjbar Sahraei
On the Skewed Degree Distribution of Hierarchical Networks. ASONAM 2015: 298-301 - [c94]Daniel Claes, Philipp Robbel, Frans A. Oliehoek, Karl Tuyls, Daniel Hennes, Wiebe van der Hoek:
Effective Approximations for Multi-Robot Coordination in Spatially Distributed Tasks. AAMAS 2015: 881-890 - [c93]Daan Bloembergen, Daniel Hennes, Simon Parsons, Karl Tuyls:
Survival of the Chartist: An Evolutionary Agent-Based Analysis of Stock Market Trading. AAMAS 2015: 1699-1700 - [c92]Bastian Broecker, Ipek Caliskanelli, Karl Tuyls, Elizabeth Sklar, Daniel Hennes:
Social Insect-Inspired Multi-Robot Coverage. AAMAS 2015: 1775-1776 - [c91]Rik Claessens, Alta de Waal, Johan Pieter de Villiers, Ate Penders, Gregor Pavlin, Karl Tuyls:
Multi-Agent Target Tracking using Particle Filters enhanced with Context Data: (Demonstration). AAMAS 2015: 1933-1934 - [c90]Eric Schneider, Elizabeth I. Sklar, M. Q. Azhar, Simon Parsons, Karl Tuyls
Towards a methodology for describing the relationship between simulation and reality. ECAL 2015: 562-569 - [c89]Joscha-David Fossel, Karl Tuyls
2D-SDF-SLAM: A signed distance function based SLAM frontend for laser scanners. IROS 2015: 1949-1955 - [c88]Bijan Ranjbar Sahraei, Julia Efremova, Hossein Rahmani, Toon Calders, Karl Tuyls
HiDER: Query-Driven Entity Resolution for Historical Data. ECML/PKDD (3) 2015: 281-284 - [c87]Bastian Broecker, Ipek Caliskanelli, Karl Tuyls
Hybrid Insect-Inspired Multi-Robot Coverage in Complex Environments. TAROS 2015: 56-68 - [p5]Julia Efremova, Bijan Ranjbar Sahraei, Hossein Rahmani, Frans A. Oliehoek, Toon Calders, Karl Tuyls
Multi-Source Entity Resolution for Genealogical Data. Population Reconstruction 2015: 129-154 - [e8]Clare Dixon
Towards Autonomous Robotic Systems - 16th Annual Conference, TAROS 2015, Liverpool, UK, September 8-10, 2015, Proceedings. Lecture Notes in Computer Science 9287, Springer 2015, ISBN 978-3-319-22415-2 [contents] - 2014
- [j20]Mihail Mihaylov, Karl Tuyls
A decentralized approach for convention emergence in multi-agent systems. Auton. Agents Multi Agent Syst. 28(5): 749-778 (2014) - [j19]Haitham Bou-Ammar, Siqi Chen, Karl Tuyls
Automated Transfer for Reinforcement Learning Tasks. Künstliche Intell. 28(1): 7-14 (2014) - [j18]Siqi Chen, Haitham Bou-Ammar, Karl Tuyls
Transfer for Automated Negotiation. Künstliche Intell. 28(1): 21-27 (2014) - [c86]Bijan Ranjbar Sahraei, Haitham Bou-Ammar, Daan Bloembergen, Karl Tuyls, Gerhard Weiss:
Theory of Cooperation in Complex Social Networks. AAAI 2014: 1471-1477 - [c85]Daan Bloembergen
Learning in Networked Interactions: A Replicator Dynamics Approach. ALIA 2014: 44-58 - [c84]Daniel Claes, Karl Tuyls
Human Robot-Team Interaction - Towards the Factory of the Future. ALIA 2014: 61-72 - [c83]Ipek Caliskanelli
Multi-Robot Coverage: A Bee Pheromone Signalling Approach. ALIA 2014: 124-140 - [c82]Bijan Ranjbar Sahraei, Dean Bloembergen, Haitham Ammar, Karl Tuyls, Gerhard Weiss:
Effects of Evolution on the Emergence of Scale Free Networks. ALIFE 2014: 376-383 - [c81]Sjriek Alers, Karl Tuyls, Bijan Ranjbar Sahraei, Daniel Claes, Gerhard Weiss:
Insect-Inspired Robot Coordination: Foraging and Coverage. ALIFE 2014: 761-768 - [c80]Siqi Chen, Shuang Zhou, Gerhard Weiss, Karl Tuyls
Using Transfer Learning to Model Unknown Opponents in Automated Negotiations. ANAC@AAMAS 2014: 175-192 - [c79]Bijan Ranjbar Sahraei, Haitham Bou-Ammar, Daan Bloembergen, Karl Tuyls, Gerhard Weiss:
Evolution of cooperation in arbitrary complex networks. AAMAS 2014: 677-684 - [c78]Sjriek Alers, Daniel Claes, Joscha-David Fossel, Daniel Hennes, Karl Tuyls:
Applied robotics: precision placement in RoboCup@Work. AAMAS 2014: 1681-1682 - [c77]Sjriek Alers, Daniel Claes, Karl Tuyls, Gerhard Weiss:
Biologically inspired multi-robot foraging. AAMAS 2014: 1683-1684 - [c76]Daan Bloembergen, Bijan Ranjbar Sahraei
Influencing Social Networks: An Optimal Control Study. ECAI 2014: 105-110 - [c75]Siqi Chen, Jianye Hao, Gerhard Weiss, Karl Tuyls
Spatial evolutionary game-theoretic perspective on agent-based complex negotiations. ECAI 2014: 983-984 - [c74]Siqi Chen, Jianye Hao, Gerhard Weiss, Karl Tuyls
Evaluating Practical Automated Negotiation Based on Spatial Evolutionary Game Theory. KI 2014: 147-158 - [c73]Hossein Rahmani, Bijan Ranjbar Sahraei, Gerhard Weiss, Karl Tuyls:
Contextual Entity Resolution Approach for Genealogical Data. LWA 2014: 168-179 - [c72]Jianye Hao, Siqi Chen, Gerhard Weiss, Ho-fung Leung, Karl Tuyls
Robustness Analysis of Negotiation Strategies through Multiagent Learning in Repeated Negotiation Games. MATES 2014: 41-56 - [c71]Bastian Broecker, Daniel Claes, Joscha-David Fossel, Karl Tuyls
Winning the RoboCup@Work 2014 Competition: The smARTLab Approach. RoboCup 2014: 142-154 - [i2]Steven de Jong, Simon Uyttendaele, Karl Tuyls:
Learning to Reach Agreement in a Continuous Ultimatum Game. CoRR abs/1401.3465 (2014) - 2013
- [c70]Sjriek Alers, Daan Bloembergen, Daniel Claes, Joscha-David Fossel, Daniel Hennes, Karl Tuyls:
Telepresence Robots as a Research Platform for AI. AAAI Spring Symposium: Designing Intelligent Robots 2013 - [c69]Siqi Chen, Haitham Bou-Ammar, Karl Tuyls, Gerhard Weiss:
Optimizing complex automated negotiation using sparse pseudo-input gaussian processes. AAMAS 2013: 707-714 - [c68]Bijan Ranjbar Sahraei, Gerhard Weiss, Karl Tuyls:
A macroscopic model for multi-robot stigmergic coverage. AAMAS 2013: 1233-1234 - [c67]Joscha-David Fossel, Daniel Hennes, Sjriek Alers, Daniel Claes, Karl Tuyls:
OctoSLAM: a 3D mapping approach to situational awareness of unmanned aerial vehicles. AAMAS 2013: 1363-1364 - [c66]Bijan Ranjbar Sahraei, Sjriek Alers, Karl Tuyls, Gerhard Weiss:
StiCo in action. AAMAS 2013: 1403-1404 - [c65]Bijan Ranjbar Sahraei, Katerina Stankova
Stackelberg-based Coverage Approach in Nonconvex Environments. ECAL 2013: 462-469 - [c64]Sjriek Alers, Bijan Ranjbar Sahraei, Stefan May, Karl Tuyls
Evaluation of an Experimental Framework for Exploiting Vision in Swarm Robotics. ECAL 2013: 775-782 - [c63]Daniel Claes, Joscha-David Fossel, Bastian Broecker, Daniel Hennes
Development of an Autonomous RC-car. ICIRA (2) 2013: 108-120 - [c62]Mohammad Chami, Haitham Bou-Ammar, Holger Voos
Swarm-based evaluation of nonparametric SysML mechatronics system design. ICM 2013: 436-441 - [c61]Siqi Chen, Haitham Bou-Ammar, Karl Tuyls, Gerhard Weiss:
Conditional Restricted Boltzmann Machines for Negotiations in Highly Competitive and Complex Domains. IJCAI 2013: 69-75 - [c60]Haitham Bou-Ammar, Decebal Constantin Mocanu
Automatically Mapped Transfer between Reinforcement Learning Tasks via Three-Way Restricted Boltzmann Machines. ECML/PKDD (2) 2013: 449-464 - [c59]Sjriek Alers, Daniel Claes, Joscha-David Fossel, Daniel Hennes
How to Win RoboCup@Work? - The Swarmlab@Work Approach Revealed. RoboCup 2013: 147-158 - 2012
- [j17]Nyree Lemmens, Karl Tuyls
Stigmergic Landmark Optimization. Adv. Complex Syst. 15(8) (2012) - [j16]Karl Tuyls
Multiagent Learning: Basics, Challenges, and Prospects. AI Mag. 33(3): 41-52 (2012) - [j15]Mark H. M. Winands
Preface for the special issue on Games and AI. Entertain. Comput. 3(3): 49-50 (2012) - [j14]Mihail Mihaylov, Yann-Aël Le Borgne, Karl Tuyls
Decentralised reinforcement learning for energy-efficient scheduling in wireless sensor networks. Int. J. Commun. Networks Distributed Syst. 9(3/4): 207-224 (2012) - [c58]Daniel Hennes, Daniel Claes, Wim Meeussen, Karl Tuyls:
Multi-robot collision avoidance with localization uncertainty. AAMAS 2012: 147-154 - [c57]Haitham Bou-Ammar, Karl Tuyls, Matthew E. Taylor, Kurt Driessens, Gerhard Weiss:
Reinforcement learning transfer via sparse coding. AAMAS 2012: 383-390 - [c56]Michael Kaisers, Daan Bloembergen, Karl Tuyls:
A common gradient in multi-agent reinforcement learning. AAMAS 2012: 1393-1394 - [c55]Sjriek Alers, Daan Bloembergen, Max Bügler, Daniel Hennes, Karl Tuyls:
MITRO: an augmented mobile telepresence robot with assisted control (demonstration). AAMAS 2012: 1475-1476 - [c54]Daniel Claes, Daniel Hennes, Wim Meeussen, Karl Tuyls:
CALU: collision avoidance with localization uncertainty (demonstration). AAMAS 2012: 1495-1496 - [c53]Daniel Hennes
Evolutionary advantage of foresight in markets. GECCO 2012: 943-950 - [c52]Daniel Claes, Daniel Hennes
Collision avoidance under bounded localization uncertainty. IROS 2012: 1192-1198 - [c51]Haitham Bou-Ammar, Karl Tuyls
Evolutionary Dynamics of Ant Colony Optimization. MATES 2012: 40-52 - [c50]Marcel Neumann, Karl Tuyls
Using Time as a Strategic Element in Continuous Double Auctions. MATES 2012: 106-115 - [e7]Massimo Cossentino
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 [contents] - 2011
- [j13]Steven de Jong, Karl Tuyls
Human-inspired computational fairness. Auton. Agents Multi Agent Syst. 22(1): 103-126 (2011) - [c49]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 - [c48]Mihail Mihaylov, Yann-Aël Le Borgne, Karl Tuyls, Ann Nowé:
Distributed cooperation in wireless sensor networks. AAMAS 2011: 249-256 - [c47]Steven de Jong, Daniel Hennes, Karl Tuyls, Ya'akov (Kobi) Gal:
Metastrategies in the Colored Trails game. AAMAS 2011: 551-558 - [c46]Daan Bloembergen, Michael Kaisers, Karl Tuyls:
Empirical and theoretical support for lenient learning. AAMAS 2011: 1105-1106 - [c45]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 - [c44]Haitham Bou-Ammar, Matthew E. Taylor, Karl Tuyls
Reinforcement Learning Transfer Using a Sparse Coded Inter-task Mapping. EUMAS 2011: 1-16 - [c43]Michael Kaisers, Daan Bloembergen
Multi-agent Learning and the Reinforcement Gradient. EUMAS 2011: 145-159 - [c42]Mihail Mihaylov, Yann-Aël Le Borgne, Ann Nowé, Karl Tuyls:
Self-organizing Synchronicity and Desynchronicity using Reinforcement Learning. ICAART (2) 2011: 94-103 - [c41]Mihail Mihaylov, Yann-Aël Le Borgne, Karl Tuyls
Reinforcement Learning for Self-organizing Wake-Up Scheduling in Wireless Sensor Networks. ICAART (Revised Selected Papers) 2011: 382-396 - 2010
- [j12]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 Jr., Darsana P. Josyula
Reports of the AAAI 2010 Conference Workshops. AI Mag. 31(4): 95-108 (2010) - [c40]Michael Kaisers, Karl Tuyls
Frequency adjusted multi-agent Q-learning. AAMAS 2010: 309-316 - [c39]Nyree Lemmens, Karl Tuyls
Stigmergic landmark routing: a routing algorithm for wireless mobile ad-hoc networks. GECCO 2010: 47-54 - [c38]Tomas Klos, Gerrit Jan van Ahee, Karl Tuyls
Evolutionary Dynamics of Regret Minimization. ECML/PKDD (2) 2010: 82-96 - [p4]Marc J. V. Ponsen, Tom Croonenborghs, Karl Tuyls
Learning with Whom to Communicate Using Relational Reinforcement Learning. Interactive Collaborative Information Systems 2010: 45-63 - [e6]Matthew E. Taylor, Karl Tuyls
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 [contents]
2000 – 2009
- 2009
- [j11]Marc J. V. Ponsen, Karl Tuyls
An evolutionary game-theoretic analysis of poker strategies. Entertain. Comput. 1(1): 39-45 (2009) - [c37]Marc J. V. Ponsen, Matthew E. Taylor
Abstraction and Generalization in Reinforcement Learning: A Summary and Framework. ALA 2009: 1-32 - [c36]Michael Kaisers, Karl Tuyls
Replicator Dynamics for Multi-agent Learning: An Orthogonal Approach. ALA 2009: 49-59 - [c35]Mihail Mihaylov, Karl Tuyls
Decentralized Learning in Wireless Sensor Networks. ALA 2009: 60-73 - [c34]Nyree Lemmens, Karl Tuyls
Stigmergic landmark foraging. AAMAS (1) 2009: 497-504 - [c33]Daniel Hennes, Karl Tuyls
State-coupled replicator dynamics. AAMAS (2) 2009: 789-796 - [c32]Steven de Jong, Karl Tuyls
Learning to cooperate in a continuous tragedy of the commons. AAMAS (2) 2009: 1185-1186 - [c31]Marc J. V. Ponsen, Tom Croonenborghs, Karl Tuyls
Learning with whom to communicate using relational reinforcement learning. AAMAS (2) 2009: 1221-1222 - [c30]Michael Kaisers, Karl Tuyls
An evolutionary model of multi-agent learning with a varying exploration rate. AAMAS (2) 2009: 1255-1256 - [p3]Ronald L. Westra, Karl Tuyls:
Replicator Dynamics in Discrete and Continuous Strategy Spaces. Multi-Agent Systems 2009: 215-241 - 2008
- [j10]Ben Torben-Nielsen
EvOL-Neuron: Neuronal morphology generation. Neurocomputing 71(4-6): 963-972 (2008) - [j9]Steven de Jong, Simon Uyttendaele, Karl Tuyls
Learning to Reach Agreement in a Continuous Ultimatum Game. J. Artif. Intell. Res. 33: 551-574 (2008) - [j8]Liviu Panait, Karl Tuyls
Theoretical Advantages of Lenient Learners: An Evolutionary Game Theoretic Perspective. J. Mach. Learn. Res. 9: 423-457 (2008) - [j7]Steven de Jong, Karl Tuyls
Fairness in multi-agent systems. Knowl. Eng. Rev. 23(2): 153-180 (2008) - [c29]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 - [c28]Peter Vrancx, Karl Tuyls
Switching dynamics of multi-agent learning. AAMAS (1) 2008: 307-313 - [c27]Steven de Jong, Karl Tuyls
Artificial agents learning human fairness. AAMAS (2) 2008: 863-870 - [c26]Daniel Hennes
Formalizing Multi-state Learning Dynamics. IAT 2008: 266-272 - [c25]Michael Kaisers, Karl Tuyls
Auction Analysis by Normal Form Game Approximation. IAT 2008: 447-450 - [c24]Matthias Rauterberg
Entertainment Computing in the Orbit. ECS 2008: 59-70 - [p2]Karl Tuyls
Introduction to Game Theory. Wiley Encyclopedia of Computer Science and Engineering 2008 - [p1]H. H. L. M. Donkers, Karl Tuyls
Belief Networks for Bioinformatics. Computational Intelligence in Bioinformatics 2008: 75-111 - [e5]Karl Tuyls
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 [contents] - [i1]Bart Kuijpers, Vanessa Lemmens, Bart Moelans
Privacy Preserving ID3 over Horizontally, Vertically and Grid Partitioned Data. CoRR abs/0803.1555 (2008) - 2007
- [j6]Katja Verbeeck, Ann Nowé, Johan Parent, Karl Tuyls
Exploring selfish reinforcement learning in repeated games with stochastic rewards. Auton. Agents Multi Agent Syst. 14(3): 239-269 (2007) - [j5]Karl Tuyls
What evolutionary game theory tells us about multiagent learning. Artif. Intell. 171(7): 406-416 (2007) - [j4]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) - [c23]Steven de Jong, Karl Tuyls
Priority Awareness: Towards a Computational Model of Human Fairness for Multi-agent Systems. Adaptive Agents and Multi-Agents Systems 2007: 117-128 - [c22]Nyree Lemmens, Steven de Jong, Karl Tuyls
Bee Behaviour in Multi-agent Systems. Adaptive Agents and Multi-Agents Systems 2007: 145-156 - [c21]Liviu Panait, Karl Tuyls
Theoretical advantages of lenient Q-learners: an evolutionary game theoretic perspective. AAMAS 2007: 40 - [c20]H. Jaap van den Herik, Daniel Hennes, Michael Kaisers, Karl Tuyls
Multi-agent Learning Dynamics: A Survey. CIA 2007: 36-56 - [c19]Goele Hollanders, Geert Jan Bex, Marc Gyssens
On Phase Transitions in Learning Sparse Networks. ECML 2007: 591-599 - [e4]Karl Tuyls
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 [contents] - 2006
- [j3]Karl Tuyls
An Evolutionary Dynamical Analysis of Multi-Agent Learning in Iterated Games. Auton. Agents Multi Agent Syst. 12(1): 115-153 (2006) - [c18]Steven de Jong, Karl Tuyls
Robust and Scalable Coordination of Potential-Field Driven Agents. CIMCA/IAWTIC 2006: 230 - [c17]Ben Torben-Nielsen, Karl Tuyls
Shaping Realistic Neuronal Morphologies: An Evolutionary Computation Method. IJCNN 2006: 573-580 - [c16]Ronald L. Westra, Karl Tuyls
Knowledge Discovery and Emergent Complexity in Bioinformatics. KDECB 2006: 1-9 - [c15]Ben Torben-Nielsen, Karl Tuyls
On the Neuronal Morphology-Function Relationship: A Synthetic Approach. KDECB 2006: 131-144 - [c14]Ronald L. Westra, Goele Hollanders, Geert Jan Bex, Marc Gyssens
The Identification of Dynamic Gene-Protein Networks. KDECB 2006: 157-170 - [c13]Geert Jan Bex, Frank Neven, Thomas Schwentick, Karl Tuyls:
Inference of Concise DTDs from XML Data. VLDB 2006: 115-126 - [e3]Karl Tuyls
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 [contents] - 2005
- [j2]Karl Tuyls
Evolutionary game theory and multi-agent reinforcement learning. Knowl. Eng. Rev. 20(1): 63-90 (2005) - [c12]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 - [c11]Katja Verbeeck, Ann Nowé, Karl Tuyls
Coordinated exploration in multi-agent reinforcement learning: an application to load-balancing. AAMAS 2005: 1105-1106 - [c10]Bart De Vylder, Karl Tuyls:
Towards a Common Lexicon in The Naming Game: The Dynamics of Synonymy Reduction. BNAIC 2005: 112-119 - [c9]Karl Tuyls, Bart Kuijpers:
Privacy in Multi-Agent Learning: Securely Inducing a Multi-Agent Decision Tree. EUMAS 2005: 427-438 - [c8]Pieter Jan't Hoen, Karl Tuyls
An Overview of Cooperative and Competitive Multiagent Learning. LAMAS 2005: 1-46 - [c7]Tom Croonenborghs, Karl Tuyls
Multi-agent Relational Reinforcement Learning. LAMAS 2005: 192-206 - [e2]Katja Verbeeck, Karl Tuyls, Ann Nowé, Bernard Manderick, Bart Kuijpers:
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 [contents] - [e1]Marie-Pierre Gleizes, Gal A. Kaminka, Ann Nowé, Sascha Ossowski, Karl Tuyls, Katja Verbeeck:
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 [contents] - 2004
- [j1]Karl Tuyls
An Evolutionary Game Theoretic Perspective on Learning in Multi-Agent Systems. Synth. 139(2): 297-330 (2004) - [c6]Pieter Jan't Hoen, Karl Tuyls
Analyzing Multi-agent Reinforcement Learning Using Evolutionary Dynamics. ECML 2004: 168-179 - 2003
- [c5]Karl Tuyls
A selection-mutation model for q-learning in multi-agent systems. AAMAS 2003: 693-700 - [c4]Karl Tuyls
On a Dynamical Analysis of Reinforcement Learning in Games: Emergence of Occam's Razor. CEEMAS 2003: 335-344 - [c3]Karl Tuyls
Extended Replicator Dynamics as a Key to Reinforcement Learning in Multi-agent Systems. ECML 2003: 421-431 - 2002
- [c2]Karl Tuyls, Sam Maes, Bernard Manderick:
Q-Learning in Simulated Robotic Soccer - Large State Spaces and Incomplete Information. ICMLA 2002: 226-232 - [c1]Karl Tuyls
Reinforcement Learning in Large State Spaces. RoboCup 2002: 319-326
Coauthor Index
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