On SAT-Based Approaches for Multi-Agent Path Finding with the Sum-of-Costs Objective

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F19%3A10408110" target="_blank" >RIV/00216208:11320/19:10408110 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

On SAT-Based Approaches for Multi-Agent Path Finding with the Sum-of-Costs Objective

Popis výsledku v původním jazyce

Multi-Agent Path Finding (MAPF) deals with the problem of finding collision-free paths for a set of agents. Each agent moves from its start location to its destination location in a shared environment represented by a graph. Reductionbased solving approaches for MAPF, for example, reduction to SAT, exploit a time-expanded layered graph, where each layer corresponds to specific time. Hence, these approaches are natural for minimizing Makespan (the shortest time until all agents reach their destinations). Modeling the other frequently used objective, namely Sum of Costs (SoC; the sum of paths lengths of all agents) is more difficult as the solution with the smallest SoC may not be reached in the timeexpanded graph with the smallest Makespan. In this paper we suggest a novel approach to estimate the Makespan, that guarantees the existence of a SoC-optimal solution. We also propose a novel pre-processing technique reducing the number of variables in the SAT model. The approach is empirically compared with an existing reduction-based method as well as with the state-of-the-art search-based optimal MAPF solver.

Název v anglickém jazyce

On SAT-Based Approaches for Multi-Agent Path Finding with the Sum-of-Costs Objective

Popis výsledku anglicky

Multi-Agent Path Finding (MAPF) deals with the problem of finding collision-free paths for a set of agents. Each agent moves from its start location to its destination location in a shared environment represented by a graph. Reductionbased solving approaches for MAPF, for example, reduction to SAT, exploit a time-expanded layered graph, where each layer corresponds to specific time. Hence, these approaches are natural for minimizing Makespan (the shortest time until all agents reach their destinations). Modeling the other frequently used objective, namely Sum of Costs (SoC; the sum of paths lengths of all agents) is more difficult as the solution with the smallest SoC may not be reached in the timeexpanded graph with the smallest Makespan. In this paper we suggest a novel approach to estimate the Makespan, that guarantees the existence of a SoC-optimal solution. We also propose a novel pre-processing technique reducing the number of variables in the SAT model. The approach is empirically compared with an existing reduction-based method as well as with the state-of-the-art search-based optimal MAPF solver.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/GA19-02183S" target="_blank" >GA19-02183S: Chytré roje: od teorie k praxi</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the Twelfth International Symposium on Combinatorial Search

ISBN

978-1-57735-808-4

ISSN

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e-ISSN

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Počet stran výsledku

8

Strana od-do

10-17

Název nakladatele

AAAI Press

Místo vydání

neuveden

Místo konání akce

Napa

Datum konání akce

16. 7. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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