Name
Abstract | ||
|---|---|---|
Recently, several researchers have found that cost-based satisficing search with A* often runs into problems. Although some "work arounds" have been proposed to ameliorate the problem, there has not been any concerted effort to pinpoint its origin. In this paper, we argue that the origins can be traced back to the wide variance in action costs that is observed in most planning domains. We show that such cost variance misleads A* search, and that this is no trifling detail or accidental phenomenon, but a systemic weakness of the very concept of "cost-based evaluation functions + systematic search + combinatorial graphs". We show that satisficing search with sized-based evaluation functions is largely immune to this problem. |
Year | Venue | Keywords |
|---|---|---|
2011 | Clinical Orthopaedics and Related Research | artificial intelligent,evaluation function |
Field | DocType | Volume |
Graph,Satisficing,Accidental,Computer science,Considered harmful,Artificial intelligence,Phenomenon | Journal | abs/1103.3 |
Citations | PageRank | References |
6 | 0.49 | 16 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| William Cushing | 1 | 132 | 7.18 |
| J. Benton | 2 | 155 | 9.45 |
| Subbarao Kambhampati | 3 | 3453 | 450.74 |