Name
Abstract | ||
|---|---|---|
Cost-based abduction (CBA) is an important problem in reasoning under uncertainty. The CBA problem is NP-hard, and existing techniques have exponential worst-case complexity. This paper presents an admissible heuristic for CBA based on the use of linear programming to obtain an optimistic estimate of the cost-to-goal. The article then presents empirical results that indicate that the authors' method is efficient in comparison to Santos' integer linear programming method. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1080/09528130500283642 | JOURNAL OF EXPERIMENTAL & THEORETICAL ARTIFICIAL INTELLIGENCE |
Keywords | Field | DocType |
hypothetical reasoning,reasoning under uncertainty,belief revision | Mathematical optimization,Exponential function,Computer science,Admissible heuristic,Integer programming,Linear programming,Belief revision | Journal |
Volume | Issue | ISSN |
17 | 3 | 0952-813X |
Citations | PageRank | References |
1 | 0.35 | 9 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ashraf M. Abdelbar | 1 | 243 | 25.43 |
| Mohamed Hefny | 2 | 1 | 0.35 |