Technical Note: \cal Q-Learning
Machine Learning
The dynamics of reinforcement learning in cooperative multiagent systems
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Neuro-Dynamic Programming
Friend-or-Foe Q-learning in General-Sum Games
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Managing Multiple Case Bases: Dimensions and Issues
Proceedings of the Fifteenth International Florida Artificial Intelligence Research Society Conference
Nash q-learning for general-sum stochastic games
The Journal of Machine Learning Research
Coordination through Mutual Notification in Cooperative Multiagent Reinforcement Learning
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 3
Reinforcement Learning for Stochastic Cooperative Multi-Agent Systems
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 3
Scheduling: Theory, Algorithms, and Systems
Scheduling: Theory, Algorithms, and Systems
Simultaneous adversarial multi-robot learning
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Collaborative case retention strategies for CBR agents
ICCBR'03 Proceedings of the 5th international conference on Case-based reasoning: Research and Development
The virtue of reward: performance, reinforcement and discovery in case-based reasoning
ICCBR'05 Proceedings of the 6th international conference on Case-Based Reasoning Research and Development
CBR for state value function approximation in reinforcement learning
ICCBR'05 Proceedings of the 6th international conference on Case-Based Reasoning Research and Development
Cooperative reuse for compositional cases in multi-agent systems
ICCBR'05 Proceedings of the 6th international conference on Case-Based Reasoning Research and Development
Evaluating the effectiveness of exploration and accumulated experience in automatic case elicitation
ICCBR'05 Proceedings of the 6th international conference on Case-Based Reasoning Research and Development
Analogical and case-based reasoning for predicting satellite task schedulability
ICCBR'05 Proceedings of the 6th international conference on Case-Based Reasoning Research and Development
Learning with case-injected genetic algorithms
IEEE Transactions on Evolutionary Computation
Case-Based Multiagent Reinforcement Learning: Cases as Heuristics for Selection of Actions
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
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In both research fields, Case-Based Reasoning and Reinforcement Learning, the system under consideration gains its expertise from experience. Utilizing this fundamental common ground as well as further characteristics and results of these two disciplines, in this paper we develop an approach that facilitates the distributed learning of behaviour policies in cooperative multi-agent domains without communication between the learning agents. We evaluate our algorithms in a case study in reactive production scheduling.