Abstract | ||
---|---|---|
One of the most promising trends in Domain-Independent AI Planning, nowadays, is state-space heuristic planning. The planners of this category construct general but efficient heuristic functions, which are used as a guide to traverse the state space either in a forward or in a backward direction. Although specific problems may favor one or the other direction, there is no clear evidence why any of them should be generally preferred. This paper presents Hybrid-AcE, a domain-independent planning system that combines search in both directions utilizing a complex criterion that monitors the progress of the search, to switch between them. Hybrid AcE embodies two powerful domain-independent heuristic functions extending one of the AcE planning systems. Moreover, the system is equipped with a fact-ordering technique and two methods for problem simplification that limit the search space and guide the algorithm to the most promising states. The bi-directional system has been tested on a variety of problems adopted from the AIPS planning competitions with quite promising results. |
Year | DOI | Venue |
---|---|---|
2005 | 10.1111/j.1467-8640.2005.00275.x | COMPUTATIONAL INTELLIGENCE |
Keywords | Field | DocType |
planning, heuristic search, bi-directional search | Incremental heuristic search,Heuristic,Mathematical optimization,Search algorithm,Computer science,Beam search,Artificial intelligence,Null-move heuristic,Best-first search,Automated planning and scheduling,Machine learning,Consistent heuristic | Journal |
Volume | Issue | ISSN |
21 | 3 | 0824-7935 |
Citations | PageRank | References |
2 | 0.43 | 17 |
Authors | ||
2 |
Name | Order | Citations | PageRank |
---|---|---|---|
Dimitris Vrakas | 1 | 251 | 23.98 |
Ioannis P. Vlahavas | 2 | 775 | 92.68 |