Title :
Compact Representations of Cooperative Path-Finding as SAT Based on Matchings in Bipartite Graphs
Author_Institution :
Charles Univ. Prague, Prague, Czech Republic
Abstract :
This paper addresses make span optimal solving of cooperative path-finding problem (CPF) by translating it to propositional satisfiability (SAT). The task is to relocate set of agents to given goal positions so that they do not collide with each other. A novel SAT encoding of CPF is suggested. The novel encoding uses the concept of matching in a bipartite graph to separate spatial constraint of CPF from consideration of individual agents. The separation allowed reducing the size of encoding significantly. The conducted experimental evaluation shown that novel encoding can be solved faster than existing encodings for CPF and also that the SAT based methods dominates over A* based methods in environment densely occupied by agents.
Keywords :
computability; graph theory; graphs; CPF; SAT based methods; SAT encoding; bipartite graphs; compact representations; cooperative path-finding problem; matchings; propositional satisfiability; Bipartite graph; Computational modeling; Cost accounting; Encoding; Materials; Planning; Vectors; A; bipartite graphs; cooperative path-finding (CPF); encodings; matchings; propositional satisfiability (SAT);
Conference_Titel :
Tools with Artificial Intelligence (ICTAI), 2014 IEEE 26th International Conference on
Conference_Location :
Limassol
DOI :
10.1109/ICTAI.2014.134