Paper Info
Title
Policy Iteration Q-Learning for Data-Based Two-Player Zero-Sum Game of Linear Discrete-Time Systems.
Abstract
In this article, the data-based two-player zero-sum game problem is considered for linear discrete-time systems. This problem theoretically depends on solving the discrete-time game algebraic Riccati equation (DTGARE), while it requires complete system dynamics. To avoid solving the DTGARE, the $Q$ -function is introduced and a data-based policy iteration $Q$ -learning (PIQL) algorithm is develo...
Year
DOI
Venue
2021
10.1109/TCYB.2020.2970969
IEEE Transactions on Cybernetics
Keywords
DocType
Volume
Games,Game theory,Gold,Heuristic algorithms,Discrete-time systems,Convergence,Dynamic programming
Journal
51
Issue
ISSN
Citations 
7
2168-2267
7
PageRank 
References 
Authors
0.45
26
3
Name
Order
Citations
PageRank
Biao Luo155423.80
Yin Yang2100352.10
Derong Liu35457286.88