Case-Based Merging Techniques in OAKPLAN

TL;DR

This paper explores case-based planning in OAKPLAN, demonstrating that reusing similar past plans can be effective despite theoretical complexity limitations, offering a practical alternative to plan generation.

Contribution

It shows that case-based planning can be efficient in practice when suitable reuse candidates are selected, despite worst-case complexity constraints.

Findings

Case-based planning can outperform plan generation with good reuse candidate selection.

Theoretical complexity does not preclude practical efficiency of case reuse.

Reusing previous plans is a viable strategy in OAKPLAN for similar problems.

Abstract

Case-based planning can take advantage of former problem-solving experiences by storing in a plan library previously generated plans that can be reused to solve similar planning problems in the future. Although comparative worst-case complexity analyses of plan generation and reuse techniques reveal that it is not possible to achieve provable efficiency gain of reuse over generation, we show that the case-based planning approach can be an effective alternative to plan generation when similar reuse candidates can be chosen.