Case-based planning: viewing planning as a memory task
Case-based planning: viewing planning as a memory task
Learning to Improve Case Adaption by Introspective Reasoning and CBR
ICCBR '95 Proceedings of the First International Conference on Case-Based Reasoning Research and Development
Learning Adaptation Rules from a Case-Base
EWCBR '96 Proceedings of the Third European Workshop on Advances in Case-Based Reasoning
The description logic handbook: theory, implementation, and applications
The description logic handbook: theory, implementation, and applications
Debugging and repair of owl ontologies
Debugging and repair of owl ontologies
Learning adaptation knowledge to improve case-based reasoning
Artificial Intelligence
Combining description logic reasoning with ai planning for composition of web services
Combining description logic reasoning with ai planning for composition of web services
PDDL2.1: an extension to PDDL for expressing temporal planning domains
Journal of Artificial Intelligence Research
Using metaphors in game-based education
Edutainment'07 Proceedings of the 2nd international conference on Technologies for e-learning and digital entertainment
Research on CBR system based on data mining
Applied Soft Computing
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Adaptation is probably the most difficult task in Case-Based Reasoning (CBR) systems. Most techniques for adaptation propose ad-hoc solutions that require an effort on knowledge acquisition beyond typical CBR standards.In this paper we demonstrate the applicability of domain-independent planning techniques that exploit the knowledge already acquired in many knowledge-rich approaches to CBR. Those techniques are exemplified in a case-based training system that generates a 3D scenario from a declarative description of the training case.