High Performance Case-based Planning
Parallel Understanding Systems Group
Computer Science Department,
University of Maryland at College Park
In case-based planning (CBP),
previously generated plans are stored as cases in memory and can be
reused to solve similar planning problems in the future. CBP can save
considerable time over planning from scratch (generative planning),
thus offering a potential (heuristic) mechanism for handling
intractable problems. One drawback of CBP systems has been the need
for a highly structured memory that requires significant domain
engineering and complex memory indexing schemes to enable efficient
case retrieval. We are investigating the use of massively parallelism
to access large memories of hundreds or more cases. These memories
are structure-based and lack special-purpose indexing structures.
Case memories are implemented using Parka,
a massively parallel frame system.
CaPER, a domain-independent case-based planning system being tested in the domain of transport logistics planning.
CHIRON, a case-based planning system for the
domain of legal reasoning using open-textured concepts.