Name
Abstract | ||
|---|---|---|
We present a hybrid approach to Distributed Constraint Satisfaction which combines incomplete, fast, penalty-based local search with complete, slower systematic search. Thus, we propose the hybrid algorithm PenDHyb where the distributed local search algorithm DisPeL is run for a very small amount of time in order to learn about the difficult areas of the problem from the penalty counts imposed during its problem-solving. This knowledge is then used to guide the systematic search algorithm SynCBJ. Extensive empirical results in several problem classes indicate that PenDHyb is effective for large problems. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-3-540-85776-1_33 | AIMSA |
Keywords | Field | DocType |
hybrid approach,penalty-based local search,systematic search algorithm,problem class,local search algorithm,difficult area,hybrid algorithm pendhyb,slower systematic search,constraint satisfaction,large problem,hybrid systems,hybrid system,search algorithm,hybrid algorithm,local search | Search algorithm,Guided Local Search,Min-conflicts algorithm,Computer science,Theoretical computer science,Artificial intelligence,Mathematical optimization,Beam search,Constraint satisfaction problem,Difference-map algorithm,Machine learning,Best-first search,Hybrid algorithm (constraint satisfaction) | Conference |
Volume | ISSN | Citations |
5253 | 0302-9743 | 2 |
PageRank | References | Authors |
0.47 | 8 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| David Lee | 1 | 127 | 15.14 |
| Inés Arana | 2 | 14 | 4.95 |
| Hatem Ahriz | 3 | 22 | 5.20 |
| Kit-Ying Hui | 4 | 69 | 7.23 |