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.
翻译:在多试样路径发现(MAPF)中,任务是为多个代理商从初始位置到特定目标位置找到非冲突路径。MAPF代表着一个古老的人工智能问题,通常通过超常研究来解决。搜索技术的一个重要替代办法是将MAPF汇编成一种不同的形式主义,如Boolean卫星卫星卫星可探测性(SAT)。以SAT为基础的现代方法将SAT解答器视为一个外部工具,其任务是将输入的MAPF的Boolean模型的所有决定变量重新分配出去。我们在这个简短的文件中提出了一个叫DPLL(MAPF)的新编译计划,在这个计划中,对MAPF规则决定变量的部分分配进行一致性检查,将直接纳入SAT解析器。这个计划使得在SAT解答器和一致性检查程序同时工作的情况下,能够进行更加自动化的汇编,从而创建Boolean模型并搜索其令人满意的任务。