Leader-Following Multi-Agent Coordination Control Accompanied With Hierarchical Q(λ)-Learning for Pursuit

Author:

Zhu Zhe-Yang,Liu Cheng-Lin

Abstract

In this paper, we investigate a pursuit problem with multi-pursuer and single evader in a two-dimensional grid space with obstacles. Taking a different approach to previous studies, this paper aims to address a pursuit problem in which only some pursuers can directly access the evader’s position. It also proposes using a hierarchical Q(λ)-learning with improved reward, with simulation results indicating that the proposed method outperforms Q-learning.

Funder

Foundation for Innovative Research Groups of the National Natural Science Foundation of China

Publisher

Frontiers Media SA

Reference21 articles.

1. Type-2 Fuzzy Logic-Based Linguistic Pursuing Strategy Design and its Deployment to a Real-World Pursuit Evasion Game;Beke;IEEE Trans. Cybern.,2020

2. An Approach to Multi-Agent Pursuit Evasion Games Using Reinforcement Learning;Bilgin,2015

3. Hierarchical Reinforcement Learning and Decision Making;Botvinick;Curr. Opin. Neurobiol.,2012

4. A Discrete-Time Pursuit-Evasion Game in Convex Polygonal Environments;Casini;Syst. Control. Lett.,2019

5. Switched and Symmetric Pursuit/evasion Games Using Online Model Predictive Control with Application to Autonomous Aircraft;Eklund;IEEE Trans. Contr. Syst. Technol.,2012

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