A stochastic process approach for multi-agent path finding with non-asymptotic performance guarantees
type: Item
instance of: scholarly article
title: A stochastic process approach for multi-agent path finding with non-asymptotic performance guarantees
author: Xiaoyu He
author: Xueyan Tang
author: Wentong Cai
author: Jingning Li
published in: Artificial Intelligence
publication date: 2024-04-30T00:00:00Z
Mathematics Subject Classification ID: 68T42
Mathematics Subject Classification ID: 62M99
Mathematics Subject Classification ID: 90C29
zbMATH DE Number: 7840022
zbMATH Keywords: multi-agent path finding
zbMATH Keywords: non-asymptotic performance
zbMATH Keywords: stochastic process
zbMATH Keywords: multi-armed bandit problem
MaRDI profile type: Publication
cites work: Heuristic search viewed as path finding in a graph
cites work: Conflict-based search for optimal multi-agent pathfinding
cites work: The increasing cost tree search for optimal multi-agent pathfinding
cites work: Anytime Pareto local search
cites work: Introduction to Multi-Armed Bandits
cites work: Finite-time analysis of the multiarmed bandit problem
cites work: Exploration-exploitation tradeoff using variance estimates in multi-armed bandits
cites work: A survey of some simulation-based algorithms for Markov decision processes
cites work: Benchmarking optimization software with performance profiles.
Wikidata QID: Q128901159
DOI: 10.1016/J.ARTINT.2024.104084
description: scientific article; zbMATH DE number 7840022