@INPROCEEDINGS{JSvan17c,
 AUTHOR= "R. Barak and N. Zhou and R. Stern and E. Boyarski and P. Surynek",
 TITLE= "Modeling and Solving the Multi-Agent Pathfinding Problem in {Picat}",
 BOOKTITLE= "Proceedings of the International Conference on Tools with Artificial Intelligence (ICTAI)",
 PAGES= "959--966",
 YEAR= "2017",
 PDF= "http://www.picat-lang.org/papers/ictai17.pdf",
 FLAGS= ":2017:,:romanbartak:,:ronistern:,:pavelsurynek:,:eliboyarski:",
 ABSTRACT=
"The multi-agent pathfinding (MAPF) problem has attracted considerable
attention because of its relation to practical applications. In this paper, we
present a constraint-based declarative model for MAPF, together with its
implementation in Picat, a logic-based programming language. We show
experimentally that our Picat-based implementation is highly competitive and
sometimes outperforms previous approaches. Importantly, the proposed Picat
implementation is very versatile. We demonstrate this by showing how it can be
easily adapted to optimize different MAPF objectives, such as minimizing
makespan or minimizing the sum of costs, and for a range of MAPF
variants. Moreover, a Picat-based model can be automatically compiled to
several general-purpose solvers such as SAT solvers and Mixed Integer
Programming solvers (MIP). This is particularly important for MAPF because
some MAPF variants are solved more efficiently when compiled to SAT while
other variants are solved more efficiently when compiled to MIP. We analyze
these differences and the impact of different declarative models and encodings
on empirical performance."
}

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