Variable Resolution Discretization in Optimal Control
Machine Learning
Friend-or-Foe Q-learning in General-Sum Games
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Using Reinforcement Learning for Similarity Assessment in Case-Based Systems
IEEE Intelligent Systems
Nash q-learning for general-sum stochastic games
The Journal of Machine Learning Research
Retrieval, reuse, revision and retention in case-based reasoning
The Knowledge Engineering Review
CBRRoboSoc: An Efficient Planning Strategy for Robotic Soccer Using Case Based Reasoning
CIMCA '06 Proceedings of the International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce
Accelerating autonomous learning by using heuristic selection of actions
Journal of Heuristics
Half Field Offense in RoboCup Soccer: A Multiagent Reinforcement Learning Case Study
RoboCup 2006: Robot Soccer World Cup X
ICCBR '07 Proceedings of the 7th international conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Exploiting Past Experience --- Case-Based Decision Support for Soccer Agents
KI '07 Proceedings of the 30th annual German conference on Advances in Artificial Intelligence
ECCBR '08 Proceedings of the 9th European conference on Advances in Case-Based Reasoning
A case-based approach for coordinated action selection in robot soccer
Artificial Intelligence
Improving Reinforcement Learning by Using Case Based Heuristics
ICCBR '09 Proceedings of the 8th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Accelerating reinforcement learning by composing solutions of automatically identified subtasks
Journal of Artificial Intelligence Research
Heuristic selection of actions in multiagent reinforcement learning
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Transfer learning in real-time strategy games using hybrid CBR/RL
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Fast concurrent reinforcement learners
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
CBR for state value function approximation in reinforcement learning
ICCBR'05 Proceedings of the 6th international conference on Case-Based Reasoning Research and Development
Multi-agent case-based reasoning for cooperative reinforcement learners
ECCBR'06 Proceedings of the 8th European conference on Advances in Case-Based Reasoning
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This work presents a new approach that allows the use of cases in a case base as heuristics to speed up Multiagent Reinforcement Learning algorithms, combining Case-Based Reasoning (CBR) and Multiagent Reinforcement Learning (MRL) techniques. This approach, called Case-Based Heuristically Accelerated Multiagent Reinforcement Learning (CB-HAMRL), builds upon an emerging technique, Heuristic Accelerated Reinforcement Learning (HARL), in which RL methods are accelerated by making use of heuristic information. CB-HAMRL is a subset of MRL that makes use of a heuristic function H derived from a case base, in a Case-Based Reasoning manner. An algorithm that incorporates CBR techniques into the Heuristically Accelerated Minimax--Q is also proposed and a set of empirical evaluations were conducted in a simulator for the Littman's robot soccer domain, comparing the three solutions for this problem: MRL, HAMRL and CB-HAMRL. Experimental results show that using CB-HAMRL, the agents learn faster than using RL or HAMRL methods.