Compact Representation of Sets of Binary Constraints
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
Exploiting subgraph structure in multi-robot path planning
Journal of Artificial Intelligence Research
Unifying SAT-based and graph-based planning
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
A novel approach to path planning for multiple robots in bi-connected graphs
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
MAPP: a scalable multi-agent path planning algorithm with tractability and completeness guarantees
Journal of Artificial Intelligence Research
Push and swap: fast cooperative path-finding with completeness guarantees
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume One
Complete algorithms for cooperative pathfinding problems
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume One
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A novel approach to cooperative path-planning is presented. A SAT solver is used not to solve the whole instance but for optimizing the makespan of a sub-optimal solution. This approach is trying to exploit the ability of stateof- the-art SAT solvers to give a solution to relatively small instance quickly. A sub-optimal solution to the instance is obtained by some existent method first. It is then submitted to the optimization process which decomposes it into small subsequences for which optimal solutions are found by a SAT solver. The new shorter solution is subsequently obtained as concatenation of optimal subsolutions. The process is iterated until a fixed point is reached. This is the first method to produce near optimal solutions for densely populated environments; it can be also applied to domain-independent planning supposed that suboptimal planner is available.