Abstract
An algorithm that performs asynchronous backtracking on distributed CSPs, with dynamic ordering of agents is proposed, ABT\_DO. Agents propose reorderings of lower priority agents and send these proposals whenever they send assignment messages. Changes of ordering triggers a different computation of Nogoods. The dynamic ordered asynchronous backtracking algorithm uses polynomial space, similarly to standard ABT. The ABT\_DO algorithm with three different ordering heuristics is compared to standard ABT on randomly generated DisCSPs. A Nogood-triggered heuristic, inspired by dynamic backtracking, is found to outperform static order ABT by a large factor in run-time and improve the network load.
| Original language | English |
|---|---|
| Pages (from-to) | 179-197 |
| Number of pages | 19 |
| Journal | Constraints |
| Volume | 11 |
| Issue number | 2-3 |
| DOIs | |
| State | Published - 1 Jul 2006 |
Keywords
- Distributed AI
- Distributed Constraint satisfaction
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ASJC Scopus subject areas
- Software
- Discrete Mathematics and Combinatorics
- Computational Theory and Mathematics
- Artificial Intelligence