Multi-Agent Planning under Uncertainty with Monte Carlo Q-Value Function

Multi-Agent Planning under Uncertainty with Monte Carlo Q-Value Function

Decentralized partially observable Markov decision processes (Dec-POMDPs) are general multi-agent models for planning under uncertainty, but are intractable to solve. Doubly exponential growth of the search space as the horizon increases makes a brute-force search impossible. Heuristic methods can g...

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Bibliographic Details
Main Authors: Jian Zhang, Yaozong Pan, Ruili Wang, Yuqiang Fang, Haitao Yang
Format: Article
Language:English
Published: MDPI AG 2019-04-01
Series:Applied Sciences
Subjects:
multi-agent
uncertainty
Monte Carlo
Q-value function
Dec-POMDP
Online Access:https://www.mdpi.com/2076-3417/9/7/1430

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https://www.mdpi.com/2076-3417/9/7/1430

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