DPLL(MAPF): an Integration of Multi-Agent Path Finding and SAT Solving Technologies

TL;DR

This paper introduces DPLL(MAPF), a novel integrated approach combining SAT solving with MAPF consistency checking, enabling more automated and efficient path finding for multiple agents.

Contribution

The paper presents a new compilation scheme that integrates MAPF consistency checking directly into the SAT solver, improving automation and efficiency.

Findings

Enhanced integration of MAPF and SAT solving.

More automated and efficient path finding.

Potential for improved scalability in MAPF solutions.

Abstract

In multi-agent path finding (MAPF), the task is to find non-conflicting paths for multiple agents from their initial positions to given individual goal positions. MAPF represents a classical artificial intelligence problem often addressed by heuristic-search. An important alternative to search-based techniques is compilation of MAPF to a different formalism such as Boolean satisfiability (SAT). Contemporary SAT-based approaches to MAPF regard the SAT solver as an external tool whose task is to return an assignment of all decision variables of a Boolean model of input MAPF. We present in this short paper a novel compilation scheme called DPLL(MAPF) in which the consistency checking of partial assignments of decision variables with respect to the MAPF rules is integrated directly into the SAT solver. This scheme allows for far more automated compilation where the SAT solver and the consistency checking procedure work together simultaneously to create the Boolean model and to search for its satisfying assignment.