CVAE-based Far-sighted Intention Inference for Opponent Modeling in Multi-agent Reinforcement Learning

Most interactive environments are non-stationary for agents, as the behaviors of their opponents continually change, which can impair the performance of reinforcement learning algorithms. This impairment can be alleviated by modeling opponents to predict their future movements. To predict more preci...

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Bibliographic Details

Published in:	Chinese Control Conference pp. 5847 - 5851
Main Authors:	Pei, Yu, Xu, XiaoPeng, Liu, Zhong, Wang, Kuo, Zhu, Li, Wang, Dong
Format:	Conference Proceeding
Language:	English
Published:	Technical Committee on Control Theory, Chinese Association of Automation 28.07.2024
Subjects:	Analytical models Attention mechanisms conditional variational autoencoder (CVAE) Decision making Games intention inference Multi-agent reinforcement learning opponent modeling Prediction algorithms Predictive models Reinforcement learning
ISSN:	1934-1768
Online Access:	Get full text
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