Conceptual Comparison of Compilation-based Solvers for Multi-Agent Path Finding: MIP vs. SAT

The task in multi-agent path finding (MAPF) is to find paths through which agents can navigate from their starting positions to given individual goal positions. The combination of two additional requirements makes the problem challenging: (i) agents must not collide with each other and (ii) the paths must be optimal with respect to some objective. We summarize and compare main ideas of contemporary compilationbased solvers for MAPF using MIP and SAT formalisms.

[1]  Trevor Scott Standley.  Finding Optimal Solutions to Cooperative Pathfinding Problems , 2010, AAAI.

[2]  Niklas Sörensson,et al.  An Extensible SAT-solver , 2003, SAT.

[3]  Pavel Surynek,et al.  Unifying Search-Based and Compilation-Based Approaches to Multi-Agent Path Finding through Satisfiability Modulo Theories , 2019, SOCS.

[4]  Peter J. Stuckey,et al.  Lazy CBS: Implicit Conflict-Based Search Using Lazy Clause Generation , 2019, ICAPS.

[5]  Roman Barták,et al.  Constraint Processing , 2009, Encyclopedia of Artificial Intelligence.

[6]  Peter J. Stuckey,et al.  New Techniques for Pairwise Symmetry Breaking in Multi-Agent Path Finding , 2020, ICAPS.

[7]  Nathan R. Sturtevant,et al.  Conflict-based search for optimal multi-agent pathfinding , 2012, Artif. Intell..

[8]  Peter J. Stuckey,et al.  Branch-and-Cut-and-Price for Multi-Agent Pathfinding , 2019, IJCAI.

[9]  Han Zhang,et al.  Multi-Agent Path Finding with Mutex Propagation , 2020, ICAPS.

[10]  Gerd Finke,et al.  Scheduling with Discrete Resource Constraints , 2004, Handbook of Scheduling.

[11]  Cesare Tinelli,et al.  Satisfiability Modulo Theories , 2021, Handbook of Satisfiability.

[12]  Wolfgang Faber.  Answer Set Programming , 2013, Reasoning Web.

[13]  Bart Selman,et al.  Planning as Satisfiability , 1992, ECAI.

[14]  Joao Marques-Silva,et al.  GRASP: A Search Algorithm for Propositional Satisfiability , 1999, IEEE Trans. Computers.

[15]  Zohar Manna,et al.  The calculus of computation - decision procedures with applications to verification , 2007 .

[16]  David J. Rader.  Deterministic Operations Research: Models and Methods in Linear Optimization , 2010 .

[17]  David Silver,et al.  Cooperative Pathfinding , 2005, AIIDE.

[18]  Jacques Carlier,et al.  Handbook of Scheduling - Algorithms, Models, and Performance Analysis , 2004 .

[19]  Gilles Audemard,et al.  On the Glucose SAT Solver , 2018, Int. J. Artif. Intell. Tools.

[20]  Malcolm Ross Kinsella Ryan.  Exploiting Subgraph Structure in Multi-Robot Path Planning , 2008, J. Artif. Intell. Res..

[21]  Roni Stern,et al.  An Empirical Comparison of the Hardness of Multi-Agent Path Finding under the Makespan and the Sum of Costs Objectives , 2016, SOCS.

[22]  Stefan Edelkamp,et al.  Automated Planning: Theory and Practice , 2007, Künstliche Intell..