Indexing, Elaboration and Refinement: Incremental Learning of Explanatory Cases
Machine Learning - Special issue on case-based reasoning
Acquiring case adaptation knowledge: a hybrid approach
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Retrieving and reusing game plays for robot soccer
ECCBR'06 Proceedings of the 8th European conference on Advances in Case-Based Reasoning
Confidence-based policy learning from demonstration using Gaussian mixture models
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
ICCBR '07 Proceedings of the 7th international conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Team Playing Behavior in Robot Soccer: A Case-Based Reasoning Approach
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
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
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This paper presents a mechanism for acquiring a case base for a CBR system that has to deal with a limited perception of the environment. The construction of case bases in these domains is very complex and requires mechanisms for autonomously adjusting the scope of the existing cases and for acquiring new cases. The work presented in this paper addresses these two goals: to find out the "right" scope of existing cases and to introduce new cases when no appropriate solution is found. We have tested the mechanism in the robot soccer domain performing experiments, both under simulation and with real robots.