Adaptation through Planning in Knowledge Intensive CBR

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.

[1]  Alan Bundy,et al.  Planning from rich ontologies through translation betweeen representations , 2005 .

[2]  Marco Antonio Gómez-Martín,et al.  Not Yet Another Visualization Tool: Learning Compilers for Fun ? , 2006 .

[3]  Susan Craw,et al.  Learning adaptation knowledge to improve case-based reasoning , 2006, Artif. Intell..

[4]  Pedro A. González-Calero,et al.  An Ontological Approach to Develop Knowledge Intensive CBR Systems , 2007, Ontologies.

[5]  Pedro Pablo Gómez-Martín,et al.  Using Metaphors in Game-Based Education , 2007, Edutainment.

[6]  David C. Wilson,et al.  Learning to Improve Case Adaption by Introspective Reasoning and CBR , 1995, ICCBR.

[7]  Mark T. Keane,et al.  Learning Adaptation Rules from a Case-Base , 1996, EWCBR.

[8]  Barry Smyth,et al.  Advances in Case-Based Reasoning , 1996, Lecture Notes in Computer Science.

[9]  Aditya Kalyanpur,et al.  Debugging and Repair of OWL Ontologies , 2006 .

[10]  Kristian J. Hammond,et al.  Case-Based Planning: Viewing Planning as a Memory Task , 1989 .

[11]  Maria Fox,et al.  PDDL2.1: An Extension to PDDL for Expressing Temporal Planning Domains , 2003, J. Artif. Intell. Res..

[12]  Woontack Woo,et al.  Technologies for E-Learning and Digital Entertainment, Third International Conference, Edutainment 2008, Nanjing, China, June 25-27, 2008, Proceedings , 2008, Edutainment.

[13]  Marco Antonio Gómez Martín,et al.  Aprendizaje Activo en Simulaciones Interactivas , 2007 .

[14]  Evren Sirin,et al.  Combining Description Logic Reasoning with AI Planning for Composition of Web Services , 2006 .

[15]  Pedro A. González-Calero,et al.  A Substitution-based Adaptation Model , 1999, ICCBR Workshops.

[16]  Diego Calvanese,et al.  The Description Logic Handbook: Theory, Implementation, and Applications , 2003, Description Logic Handbook.