HTN planning: complexity and expressivity
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
Applying case-based reasoning: techniques for enterprise systems
Applying case-based reasoning: techniques for enterprise systems
Planning and Learning by Analogical Reasoning
Planning and Learning by Analogical Reasoning
Case Acquisition in a Project Planning Environment
ECCBR '02 Proceedings of the 6th European Conference on Advances in Case-Based Reasoning
Maintaining Unstructured Case Base
ICCBR '97 Proceedings of the Second International Conference on Case-Based Reasoning Research and Development
Refining Conversational Case Libraries
ICCBR '97 Proceedings of the Second 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
Categorizing Case-Base Maintenance: Dimensions and Directions
EWCBR '98 Proceedings of the 4th European Workshop on Advances in Case-Based Reasoning
Building and refining abstract planning cases by change of representation language
Journal of Artificial Intelligence Research
SHOP: simple hierarchical ordered planner
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Remembering to forget: a competence-preserving case deletion policy for case-based reasoning systems
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
SiN: integrating case-based reasoning with task decomposition
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Design and implementation of a replay framework based on a partial order planner
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
| Hi-index | 0.00 |
We propose an algorithm, CBM-Gen+, to refine case bases for hierarchical and incomplete domains. In these domains, the case bases are the main source of domain information because of the absence of a complete domain theory. CBM-Gen+ revises the existing cases when a new solution is captured. The main purpose of this revision is to reduce inconsistencies in the cases. We will prove that CBM-Gen+ is sound relative to the captured solutions. We also perform experiments showing that CBM-Gen+ is on average at least as efficient as a previous approach for constructing case bases for hierarchical domains.