Evaluating a Case-Based Planning System

Retrieval Algorithms: Empirical Evaluations

CAPER is a case-based planning system that makes use of the massive parallelism of the Connection Machine to access a large memory of hundreds or more cases that are not pre-indexed. Preliminary empirical results of these retrieval methods indicate their viability and scalability. These results have motivated the retrieval-intensive design of the complete system, which includes proposed plan adaptation methods that use plan validation structure information and proposed retrieval planning procedure. The design tradeoffs in the plan retrieval and adaptation processes are discussed, and criteria for empirically evaluating these processes are presented. Many of the proposed areas for evaluation apply to other case-based planning and case-based reasoning systems.