Explanation Generation for Multi-Modal Multi-Agent Path Finding with Optimal Resource Utilization using Answer Set Programming

The multi-agent path finding (MAPF) problem is a combinatorial search problem that aims at finding paths for multiple agents (e.g., robots) in an environment (e.g., an autonomous warehouse) such that no two agents collide with each other, and subject to some constraints on the lengths of paths. We c...

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Veröffentlicht in:Theory and practice of logic programming Jg. 20; H. 6; S. 974 - 989
Hauptverfasser: BOGATARKAN, AYSU, ERDEM, ESRA
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Cambridge, UK Cambridge University Press 01.11.2020
Schlagworte:
Combinatorial analysis
Declarative programming
Flexibility
Mathematical programming
Multiagent systems
Optimization
Original Article
Resource utilization
Warehouses
ISSN:1471-0684, 1475-3081
Online-Zugang:Volltext
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Zusammenfassung:The multi-agent path finding (MAPF) problem is a combinatorial search problem that aims at finding paths for multiple agents (e.g., robots) in an environment (e.g., an autonomous warehouse) such that no two agents collide with each other, and subject to some constraints on the lengths of paths. We consider a general version of MAPF, called mMAPF, that involves multi-modal transportation modes (e.g., due to velocity constraints) and consumption of different types of resources (e.g., batteries). The real-world applications of mMAPF require flexibility (e.g., solving variations of mMAPF) as well as explainability. Our earlier studies on mMAPF have focused on the former challenge of flexibility. In this study, we focus on the latter challenge of explainability, and introduce a method for generating explanations for queries regarding the feasibility and optimality of solutions, the nonexistence of solutions, and the observations about solutions. Our method is based on answer set programming.
Bibliographie:ObjectType-Article-1
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content type line 14
ISSN:1471-0684
1475-3081
DOI:10.1017/S1471068420000320