A world championship caliber checkers program
Artificial Intelligence
Graph theoretical structures in logic programs and default theories
Theoretical Computer Science
Relational reinforcement learning
Machine Learning - Special issue on inducive logic programming
Artificial Intelligence - Chips challenging champions: games, computers and Artificial Intelligence
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Efficient Theta-Subsumption Based on Graph Algorithms
ILP '96 Selected Papers from the 6th International Workshop on Inductive Logic Programming
Relational temporal difference learning
ICML '06 Proceedings of the 23rd international conference on Machine learning
Complexities of homomorphism and isomorphism for definite logic programs
Journal of Computer Science and Technology
Transfer via inter-task mappings in policy search reinforcement learning
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Automatic heuristic construction in a complete general game player
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
General game learning using knowledge transfer
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Case-Based Reasoning in Transfer Learning
ICCBR '09 Proceedings of the 8th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Generalized learning automata for multi-agent reinforcement learning
AI Communications - European Workshop on Multi-Agent Systems (EUMAS) 2009
Reinforcement learning transfer via common subspaces
ALA'11 Proceedings of the 11th international conference on Adaptive and Learning Agents
Reinforcement learning transfer via sparse coding
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Reinforcement learning transfer using a sparse coded inter-task mapping
EUMAS'11 Proceedings of the 9th European conference on Multi-Agent Systems
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A general game player is an agent capable of taking as input a description of a game's rules in a formal language and proceeding to play without any subsequent human input. To do well, an agent should learn from experience with past games and transfer the learned knowledge to new problems. We introduce a graph-based method for identifying previously encountered games and prove its robustness formally. We then describe how the same basic approach can be used to identify similar but non-identical games. We apply this technique to automate domain mapping for value function transfer and speed up reinforcement learning on variants of previously played games. Our approach is fully implemented with empirical results in the general game playing system.