Generating qualitatively different plans through metatheoretic biases
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
A Survey on Case-Based Planning
Artificial Intelligence Review
ECCBR '02 Proceedings of the 6th European Conference on Advances in Case-Based Reasoning
ICCBR '01 Proceedings of the 4th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
The Knowledge Engineering Review
The FF planning system: fast plan generation through heuristic search
Journal of Artificial Intelligence Research
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IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
ExpertClerk: navigating shoppers' buying process with the combination of asking and proposing
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
On the role of diversity in conversational recommender systems
ICCBR'03 Proceedings of the 5th international conference on Case-based reasoning: Research and Development
Kernel functions for case-based planning
Artificial Intelligence
MIST: an interactive storytelling system with variable character behavior
ICIDS'10 Proceedings of the Third joint conference on Interactive digital storytelling
Ways of computing diverse collaborative recommendations
AH'06 Proceedings of the 4th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems
Completeness criteria for retrieval in recommender systems
ECCBR'06 Proceedings of the 8th European conference on Advances in Case-Based Reasoning
ICCBR'10 Proceedings of the 18th international conference on Case-Based Reasoning Research and Development
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Plan diversity has practical value in multiple planning domains, including travel planning, military planning and game planning. Existing methods for obtaining plan diversity fall under two categories: quantitative and qualitative. Quantitative plan diversity is domain-independent and does not require extensive knowledge-engineering effort, but can fail to reflect plan differences that are truly meaningful to users. Qualitative plan diversity is based on domain-specific characteristics which human experts might use to differentiate between plans, thus being able to produce results of greater practical value. However, the previous approach to qualitative plan diversity assumes the availability of a domain metatheory. We propose a case-based planning method for obtaining qualitative plan diversity through the use of distance metrics which incorporate domain-specific content, without requiring a domain metatheory. To our knowledge, this is the first time qualitative plan diversity is being explored in a case-based planning context.