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Integration of independence detection into SAT-based optimal multi-agent path finding a novel SAT-based optimal MAPF solver

Pavel Surynek, Jiří Švancara, Ariel Felner, Eli Boyarski

The problem of optimal multi-agent path finding (MAPF) is addressed in this paper. The task is to find optimal paths for mobile agents where each of them need to reach a unique goal position from the given start with respect to the given cost function. Agents must not collide with each other which is a source of combinatorial difficulty of the problem. An abstraction of the problem where discrete agents move in an undirected graph is usually adopted in the literature. Specifically, it is shown in this paper how to integrate independence detection (ID) technique developed for search based MAPF solving into a compilation-based technique that translates the instance of the MAPF problem into propositional satisfiability formalism (SAT). The independence detection technique allows decomposition of the instance consisting of a given number of agents into instances consisting of small groups of agents with no interaction across groups. These small instances can be solved independently and the solution of the original instance is combined from small solutions eventually. The reduction of the size of instances translated to the target SAT formalism has a significant impact on performance as shown in the presented experimental evaluation. The new solver integrating SAT translation and the independence detection is shown to be state-of-the-art in its class for optimal MAPF solving.

שפת פרסום אנגלית
דפים 85-95
סטטוס פרסום פורסם - 01.01.2017

Keywords

Cost Optimality
Independence Detection (ID)
Makespan Optimality
Multi-Agent Path-Finding (MAPF)
Path-Finding on Grids
Propositional Satisfiability (SAT)
SAT Encodings
Sum-of-costs Optimality

ASJC Scopus subject areas

Artificial Intelligence
Software
Control and Systems Engineering
גישה למסמך
10.5220/0006126000850095
קבצים וקישורים אחרים
Link to publication in Scopus