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Stabilizing Multi agent Deep Reinforcement Learning by Implicitly Estimating Other Agents’ Behaviors

Abstract: 

Deep reinforcement learning (DRL) is able to learn control policies for many complicated tasks, but it’s power has not been unleashed to handle multi-agent circumstances. Independent learning, where each agent treats others as part of the environment and learns its own policy without considering others’ policies is a simple way to apply DRL to multi-agent tasks. However, since agents’ policies change as learning proceeds, from the perspective of each agent, the environment is non-stationary, which makes conventional DRL methods inefficient. To cope with this challenge, we propose a novel approach where each agent uses an implicit estimate of others’ actions to guide its own policy learning. We demonstrate that given the implicit estimate of others’ actions, each agent can learn its policy in a relatively stationary environment. Extensive experiments show that our method significantly alleviates the non-stationarity and outperforms the state-of-the-art in terms of both convergence speed and policy performance.

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Paper Details

Authors:
Yue Jin, Shuangqing Wei, Jian Yuan, Xudong Zhang, Chao Wang
Submitted On:
17 May 2020 - 8:31am
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Type:
Presentation Slides
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Document Year:
2020
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stabilizing_madrl_by_implicitly_estimating_other_agents'_behaviors.pdf

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[1] Yue Jin, Shuangqing Wei, Jian Yuan, Xudong Zhang, Chao Wang, "Stabilizing Multi agent Deep Reinforcement Learning by Implicitly Estimating Other Agents’ Behaviors", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5384. Accessed: Sep. 24, 2020.
@article{5384-20,
url = {http://sigport.org/5384},
author = {Yue Jin; Shuangqing Wei; Jian Yuan; Xudong Zhang; Chao Wang },
publisher = {IEEE SigPort},
title = {Stabilizing Multi agent Deep Reinforcement Learning by Implicitly Estimating Other Agents’ Behaviors},
year = {2020} }
TY - EJOUR
T1 - Stabilizing Multi agent Deep Reinforcement Learning by Implicitly Estimating Other Agents’ Behaviors
AU - Yue Jin; Shuangqing Wei; Jian Yuan; Xudong Zhang; Chao Wang
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5384
ER -
Yue Jin, Shuangqing Wei, Jian Yuan, Xudong Zhang, Chao Wang. (2020). Stabilizing Multi agent Deep Reinforcement Learning by Implicitly Estimating Other Agents’ Behaviors. IEEE SigPort. http://sigport.org/5384
Yue Jin, Shuangqing Wei, Jian Yuan, Xudong Zhang, Chao Wang, 2020. Stabilizing Multi agent Deep Reinforcement Learning by Implicitly Estimating Other Agents’ Behaviors. Available at: http://sigport.org/5384.
Yue Jin, Shuangqing Wei, Jian Yuan, Xudong Zhang, Chao Wang. (2020). "Stabilizing Multi agent Deep Reinforcement Learning by Implicitly Estimating Other Agents’ Behaviors." Web.
1. Yue Jin, Shuangqing Wei, Jian Yuan, Xudong Zhang, Chao Wang. Stabilizing Multi agent Deep Reinforcement Learning by Implicitly Estimating Other Agents’ Behaviors [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5384