H. U. Sheikh and L. Bölöni

The Emergence of Complex Bodyguard Behavior Through Multi-Agent Reinforcement Learning


Cite as:

H. U. Sheikh and L. Bölöni. The Emergence of Complex Bodyguard Behavior Through Multi-Agent Reinforcement Learning. In Proc. of Autonomy in Teams (AIT-2018) workshop at IJCAI-2018, July 2018.

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Abstract:

In this paper we are considering a scenario where a team of robot bodyguards are providing physical protection to a VIP in a crowded public space. We show that the problem involves a complex mesh of interactions between the VIP and the robots, between the robots themselves and the robots and the bystanders respectively. We show how recently proposed multi-agent policy gradient reinforcement learning algorithms such as MADDPG can be successfully adapted to learn collaborative robot behaviors that provide protection to the VIP.

BibTeX:

@inproceedings{Sheikh-2018-AIT,
author = "H. U. Sheikh and L. B{\"o}l{\"o}ni",
booktitle={Proc. of Autonomy in Teams (AIT-2018) workshop at IJCAI-2018},
title = "The Emergence of Complex Bodyguard Behavior Through Multi-Agent Reinforcement Learning",
location = "Stockholm, Sweden",
month = "July",
year = "2018",
abstract = {
  In this paper we are considering a scenario where a team of robot bodyguards are providing physical protection to a VIP in a crowded public space. We show that the problem involves a complex mesh of interactions between the VIP and the robots, between the robots themselves and the robots and the bystanders respectively. We show how recently proposed multi-agent policy gradient reinforcement learning algorithms such as MADDPG can be successfully adapted to learn collaborative robot behaviors that provide protection to the VIP.
 }
}

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