2019
AAAI
AAAI 2019
Online Multi-Agent Pathfinding
Abstract
Abstract Multi-agent pathfinding (MAPF) is the problem of moving a group of agents to a set of target destinations while avoiding collisions. In this work, we study the online version of MAPF where new agents appear over time. Several variants of online MAPF are defined and analyzed theoretically, showing that it is not possible to create an optimal online MAPF solver. Nevertheless, we propose effective online MAPF algorithms that balance solution quality, runtime, and the number of plan changes an agent makes during execution.
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Conference Pioneer
— AAAI 2019
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Interdisciplinary Bridge
— Artificial Intelligence and Computer Science
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Keyword Pioneer
— plan change
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio