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 - Jul 2006 |
| Externally published | Yes |
Bibliographical note
Funding Information:Acknowledgments Supported by the Lynn and William Frankel Center for Computer Sciences and the Paul Ivanier Center for Robotics and Production Management.
Funding
Acknowledgments Supported by the Lynn and William Frankel Center for Computer Sciences and the Paul Ivanier Center for Robotics and Production Management.
| Funders | Funder number |
|---|---|
| Lynn and William Frankel Center for Computer Sciences |
Keywords
- Distributed AI
- Distributed Constraint satisfaction
- Search