TY - GEN
T1 - Min-domain ordering for asynchronous backtracking
AU - Zivan, Roie
AU - Zazone, Moshe
AU - Meisels, Amnon
PY - 2007
Y1 - 2007
N2 - Ordering heuristics are a powerful tool in CSP search algorithms. Among the most successful ordering heuristics are heuristics which enforce a fail first strategy by using the min-domain property [10,4,20,6]. Ordering heuristics have been introduced recently to Asynchronous backtracking (ABT), for distributed constraints satisfaction (DisCSP) [27], However, the pioneering study of dynamically ordered ABT, ABT_DO, has shown that a straightforward implementation of the min-domain heuristic does not produce the expected improvement over a static ordering. The best ordering heuristic for asynchronous backtracking was found to be the Nogood-triggered heuristic. The present paper proposes an asynchronous dynamic ordering which does not follow the standard restrictions on the position of reordered agents in ABT_DO. Agents can be moved to a position that is higher than that of the target of the backtrack {culprit). Combining the Nogood-triggered heuristic and the min-domain property in this new class of heuristics results in the best performing version of ABT_DO. The new version of retroactively ordered ABT is faster by a large factor than the best form of ABT.
AB - Ordering heuristics are a powerful tool in CSP search algorithms. Among the most successful ordering heuristics are heuristics which enforce a fail first strategy by using the min-domain property [10,4,20,6]. Ordering heuristics have been introduced recently to Asynchronous backtracking (ABT), for distributed constraints satisfaction (DisCSP) [27], However, the pioneering study of dynamically ordered ABT, ABT_DO, has shown that a straightforward implementation of the min-domain heuristic does not produce the expected improvement over a static ordering. The best ordering heuristic for asynchronous backtracking was found to be the Nogood-triggered heuristic. The present paper proposes an asynchronous dynamic ordering which does not follow the standard restrictions on the position of reordered agents in ABT_DO. Agents can be moved to a position that is higher than that of the target of the backtrack {culprit). Combining the Nogood-triggered heuristic and the min-domain property in this new class of heuristics results in the best performing version of ABT_DO. The new version of retroactively ordered ABT is faster by a large factor than the best form of ABT.
UR - http://www.scopus.com/inward/record.url?scp=38149088265&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-74970-7_53
DO - 10.1007/978-3-540-74970-7_53
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AN - SCOPUS:38149088265
SN - 3540749691
SN - 9783540749691
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 757
EP - 772
BT - Principles and Practice of Constraint Programming - CP 2007 - 13th International Conference, CP 2007, Proceedings
PB - Springer Verlag
T2 - 13th International Conference on Principles and Practice of Constraint Programming, CP 2007
Y2 - 23 September 2007 through 27 September 2007
ER -