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2020 – today

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2024
[c48]
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Ian Gemp, Marc Lanctot, Luke Marris, Yiran Mao, Edgar A. Duéñez-Guzmán, Sarah Perrin, Andras Gyorgy, Romuald Elie, Georgios Piliouras, Michael Kaisers, Daniel Hennes, Kalesha Bullard, Kate Larson, Yoram Bachrach:
Approximating the Core via Iterative Coalition Sampling. AAMAS 2024: 669-678
[i10]
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  - journals/corr/abs-2402-03928
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Ian Gemp, Marc Lanctot, Luke Marris, Yiran Mao, Edgar A. Duéñez-Guzmán, Sarah Perrin, Andras Gyorgy, Romuald Elie, Georgios Piliouras, Michael Kaisers, Daniel Hennes, Kalesha Bullard, Kate Larson, Yoram Bachrach:
Approximating the Core via Iterative Coalition Sampling. CoRR abs/2402.03928 (2024)
2023
[c47]
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Daniel Hernandez, Hendrik Baier, Michael Kaisers:
BRExIt: On Opponent Modelling in Expert Iteration. IJCAI 2023: 3795-3802
[i9]
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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)
2022
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Daniel Willemsen, Hendrik Baier, Michael Kaisers:
Value targets in off-policy AlphaZero: a new greedy backup. Neural Comput. Appl. 34(3): 1801-1814 (2022)
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Daniel Willemsen, Hendrik Baier, Michael Kaisers:
Correction to: Value targets in off-policy AlphaZero: a new greedy backup. Neural Comput. Appl. 34(23): 21407 (2022)
[c46]
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Jinke He, Miguel Suau, Hendrik Baier, Michael Kaisers, Frans A. Oliehoek:
Online Planning in POMDPs with Self-Improving Simulators. IJCAI 2022: 4628-4634
[i8]
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Jinke He, Miguel Suau, Hendrik Baier, Michael Kaisers, Frans A. Oliehoek:
Online Planning in POMDPs with Self-Improving Simulators. CoRR abs/2201.11404 (2022)
[i7]
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  - journals/corr/abs-2206-00113
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Daniel Hernandez, Hendrik Baier, Michael Kaisers:
BRExIt: On Opponent Modelling in Expert Iteration. CoRR abs/2206.00113 (2022)
2021
[c45]
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Hendrik Baier, Michael Kaisers:
Novelty and MCTS. GECCO Companion 2021: 1483-1487
[c44]
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Hendrik Baier, Michael Kaisers:
ME-MCTS: Online Generalization by Combining Multiple Value Estimators. IJCAI 2021: 4032-4038
[c43]
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Tim Baarslag, Tijmen Elfrink, Faria Nassiri Mofakham, Thimjo Koça, Michael Kaisers, Reyhan Aydogan:
Bargaining Chips: Coordinating One-to-Many Concurrent Composite Negotiations. WI/IAT 2021: 390-397
2020
[c42]
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Hendrik Baier, Michael Kaisers:
Guiding Multiplayer MCTS by Focusing on Yourself. CoG 2020: 550-557
[c41]
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Hendrik Baier, Michael Kaisers:
Opponent-Pruning Paranoid Search. FDG 2020: 10:1-10:7
[i6]
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Michael Kaisers, Matthias Klein, Alexander Klauer:
Grid-friendly Sustainable Local Energy Communities . ERCIM News 2020(121) (2020)

2010 – 2019

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2019
[c40]
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Richard Klíma, Daan Bloembergen, Michael Kaisers, Karl Tuyls:
Robust Temporal Difference Learning for Critical Domains. AAMAS 2019: 350-358
[c39]
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Georgios Methenitis, Michael Kaisers, Han La Poutré:
Forecast-Based Mechanisms for Demand Response. AAMAS 2019: 1600-1608
[c38]
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Haralambie Leahu, Michael Kaisers, Tim Baarslag:
Preference Learning in Automated Negotiation Using Gaussian Uncertainty Models. AAMAS 2019: 2087-2089
[c37]
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Shantanu Chakraborty, Pablo Hernandez-Leal, Michael Kaisers:
An Exchange Mechanism to Coordinate Flexibility in Residential Energy Cooperatives. ICIT 2019: 595-600
[c36]
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Haralambie Leahu, Michael Kaisers, Tim Baarslag:
Automated Negotiation with Gaussian Process-based Utility Models. IJCAI 2019: 421-427
[i5]
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  - journals/corr/abs-1901-08021
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Richard Klíma, Daan Bloembergen, Michael Kaisers, Karl Tuyls:
Robust temporal difference learning for critical domains. CoRR abs/1901.08021 (2019)
[i4]
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  - journals/corr/abs-1911-12303
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Shantanu Chakraborty, Tim Baarslag, Michael Kaisers:
Automated Peer-to-peer Negotiation for Energy Contract Settlements in Residential Cooperatives. CoRR abs/1911.12303 (2019)
2018
[j4]
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  - journals/eninf/MethenitisKP18
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Georgios Methenitis, Michael Kaisers, Han La Poutré:
Renewable electricity trading through SLAs. Energy Inform. 1(1) (2018)
[c35]
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Dimitrios Tsimpoukis, Tim Baarslag, Michael Kaisers, Nikolaos G. Paterakis:
Automated Negotiations Under User Preference Uncertainty: A Linear Programming Approach. AT 2018: 115-129
[c34]
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Shantanu Chakraborty, Pablo Hernandez-Leal, Michael Kaisers:
Coordinating Distributed and Flexible Resources: A Case-study of Residential Cooperatives. ISGT Europe 2018: 1-6
[c33]
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Arzam Muzaffar Kotriwala, Pablo Hernandez-Leal, Michael Kaisers:
Load Classification and Forecasting for Temporary Power Installations. ISGT Europe 2018: 1-6
[c32]
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Shantanu Chakraborty, Tim Baarslag, Michael Kaisers:
Energy Contract Settlements through Automated Negotiation in Residential Cooperatives. SmartGridComm 2018: 1-6
[i3]
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  - journals/corr/abs-1807-10978
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Shantanu Chakraborty, Tim Baarslag, Michael Kaisers:
Energy Contract Settlements through Automated Negotiation in Residential Cooperatives. CoRR abs/1807.10978 (2018)
[i2]
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  - journals/corr/abs-1812-04750
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Shantanu Chakraborty, Pablo Hernandez-Leal, Michael Kaisers:
An Exchange Mechanism to Coordinate Flexibility in Residential Energy Cooperatives. CoRR abs/1812.04750 (2018)
2017
[c31]
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Tim Baarslag, Michael Kaisers, Enrico H. Gerding, Catholijn M. Jonker, Jonathan Gratch:
Computers That Negotiate on Our Behalf: Major Challenges for Self-sufficient, Self-directed, and Interdependent Negotiating Agents. AAMAS Workshops (Visionary Papers) 2017: 143-163
[c30]
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Pablo Hernandez-Leal, Michael Kaisers:
Towards a Fast Detection of Opponents in Repeated Stochastic Games. AAMAS Workshops (Selected Papers) 2017: 239-257
[c29]
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Tim Baarslag, Michael Kaisers:
The Value of Information in Automated Negotiation: A Decision Model for Eliciting User Preferences. AAMAS 2017: 391-400
[c28]
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Georgios Methenitis, Michael Kaisers, Han La Poutré:
SLA-Mechanisms for Electricity Trading under Volatile Supply and Varying Criticality of Demand. AAMAS 2017: 1640-1642
[c27]
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Tim Baarslag, Michael Kaisers, Enrico H. Gerding, Catholijn M. Jonker, Jonathan Gratch:
When Will Negotiation Agents Be Able to Represent Us? The Challenges and Opportunities for Autonomous Negotiators. IJCAI 2017: 4684-4690
[i1]
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Pablo Hernandez-Leal, Michael Kaisers, Tim Baarslag, Enrique Munoz de Cote:
A Survey of Learning in Multiagent Environments: Dealing with Non-Stationarity. CoRR abs/1707.09183 (2017)
2016
[j3]
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Sherief Abdallah, Michael Kaisers:
Addressing Environment Non-Stationarity by Repeating Q-learning Updates. J. Mach. Learn. Res. 17: 46:1-46:31 (2016)
[c26]
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Timon V. Kanters, Frans A. Oliehoek, Michael Kaisers, Stan R. van den Bosch, Joep Grispen, Jeroen Hermans:
Energy- and Cost-Efficient Pumping Station Control. AAAI 2016: 3842-3848
[c25]
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Georgios Methenitis, Michael Kaisers, Han La Poutré:
Incentivizing Intelligent Customer Behavior in Smart-Grids: A Risk-Sharing Tariff & Optimal Strategies. IJCAI 2016: 380-386
[c24]
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Felix N. Claessen, Michael Kaisers, Han La Poutré:
Efficient balancing by effort-based activation of demand response services. ISGT Europe 2016: 1-6
[c23]
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Aliene van der Veen, Michael Kaisers:
Computing the value of flexibility in electricity retail, ahead and balancing markets. ISGT Europe 2016: 1-6
2015
[j2]
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Daan Bloembergen, Karl Tuyls, Daniel Hennes, Michael Kaisers:
Evolutionary Dynamics of Multi-Agent Learning: A Survey. J. Artif. Intell. Res. 53: 659-697 (2015)
[c22]
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Tobias Linnenberg, Alexander Fay, Michael Kaisers:
Bottom-Up Demand Response by Following Local Energy Generation Voluntarily. AAAI 2015: 4282-4283
[c21]
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Felix Claessen, Bart Liefers, Michael Kaisers, Han La Poutré:
The value of online information for demand response in Walrasian electricity markets. ISGT Asia 2015: 1-6
[c20]
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Georgios Methenitis, Michael Kaisers, Han La Poutré:
A multi-scale energy demand model suggests sharing market risks with intelligent energy cooperatives. ISGT Asia 2015: 1-6
[c19]
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Sherief Abdallah, Michael Kaisers:
Improving Multi-agent Learners Using Less-Biased Value Estimators. WI-IAT (2) 2015: 120-124
2013
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Marco Lützenberger, Tobias Küster, Thomas Konnerth, Alexander Thiele, Nils Masuch, Axel Heßler, Jan Keiser, Michael Burkhardt, Silvan Kaiser, Jakob Tonn, Michael Kaisers, Sahin Albayrak:
A Multi-agent Approach to Professional Software Engineering. EMAS@AAMAS 2013: 156-175
[c17]
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Sherief Abdallah, Michael Kaisers:
Addressing the policy-bias of q-learning by repeating updates. AAMAS 2013: 1045-1052
2012
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  - conf/aamas/WunderYKL12
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Michael Wunder, John Robert Yaros, Michael Kaisers, Michael L. Littman:
A framework for modeling population strategies by depth of reasoning. AAMAS 2012: 947-954
[c15]
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Michael Kaisers, Daan Bloembergen, Karl Tuyls:
A common gradient in multi-agent reinforcement learning. AAMAS 2012: 1393-1394
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Daniel Hennes, Daan Bloembergen, Michael Kaisers, Karl Tuyls, Simon Parsons:
Evolutionary advantage of foresight in markets. GECCO 2012: 943-950
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  - conf/mates/Bou-AmmarTK12
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Haitham Bou-Ammar, Karl Tuyls, Michael Kaisers:
Evolutionary Dynamics of Ant Colony Optimization. MATES 2012: 40-52
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Marcel Neumann, Karl Tuyls, Michael Kaisers:
Using Time as a Strategic Element in Continuous Double Auctions. MATES 2012: 106-115
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  - conf/eumas/2011
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Massimo Cossentino, Michael Kaisers, Karl Tuyls, Gerhard Weiss:
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
[c11]
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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
[c10]
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Michael Wunder, Michael Kaisers, John Robert Yaros, Michael L. Littman:
Using iterated reasoning to predict opponent strategies. AAMAS 2011: 593-600
[c9]
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  - conf/atal/BloembergenKT11
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Daan Bloembergen, Michael Kaisers, Karl Tuyls:
Empirical and theoretical support for lenient learning. AAMAS 2011: 1105-1106
[c8]
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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
[c7]
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  - conf/eumas/KaisersBT11
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Michael Kaisers, Daan Bloembergen, Karl Tuyls:
Multi-agent Learning and the Reinforcement Gradient. EUMAS 2011: 145-159
2010
[c6]
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Michael Wunder, Michael L. Littman, Michael Kaisers, John Robert Yaros:
A Cognitive Hierarchy Model Applied to the Lemonade Game. Interactive Decision Theory and Game Theory 2010
[c5]
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Michael Kaisers, Karl Tuyls:
Frequency adjusted multi-agent Q-learning. AAMAS 2010: 309-316

2000 – 2009

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2009
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Marc J. V. Ponsen, Karl Tuyls, Michael Kaisers, Jan Ramon:
An evolutionary game-theoretic analysis of poker strategies. Entertain. Comput. 1(1): 39-45 (2009)
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Michael Kaisers, Karl Tuyls:
Replicator Dynamics for Multi-agent Learning: An Orthogonal Approach. ALA 2009: 49-59
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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
2008
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Michael Kaisers, Karl Tuyls, Frank Thuijsman, Simon Parsons:
Auction Analysis by Normal Form Game Approximation. IAT 2008: 447-450
2007
[c1]
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  - conf/cia/HerikHKTV07
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H. Jaap van den Herik, Daniel Hennes, Michael Kaisers, Karl Tuyls, Katja Verbeeck:
Multi-agent Learning Dynamics: A Survey. CIA 2007: 36-56

Coauthor Index

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