A Data-Driven Modeling Method for Game Adversity Agent

Authors

Zeng Bi, 1. Beijing Simulation Center, Beijing 100854, China; ;2. Beijing Institute of Electronic System, Beijing 100854, China; ;
Fang Xiao, 1. Beijing Simulation Center, Beijing 100854, China; ;
Deshuai Kong, 3. China Aerospace Science and Industry Corporation Limited, Beijing 100048, China;
Xiangxiang Song, 1. Beijing Simulation Center, Beijing 100854, China; ;
Zhengxuan Jia, 1. Beijing Simulation Center, Beijing 100854, China; ;2. Beijing Institute of Electronic System, Beijing 100854, China; ;
Tingyu Lin, 1. Beijing Simulation Center, Beijing 100854, China; ;2. Beijing Institute of Electronic System, Beijing 100854, China; ;

Abstract

Abstract: Aiming at the problems of collaborative modeling of formation behavior and intelligent generation of decision-making in complex confrontation scenarios, based on the serious game to simulate the confrontation scenarios of complex maritime equipment against the air, this paper proposes a data-driven modeling method for game agent and uses a distributed modeling technology of parallel adversarial scenarios and opportunistic decision making technology of smart targets to achieve agent modeling. It provides support for the further exploration of multi-objective collaborative modeling in complex confrontation scenarios. The simulation results show that deep reinforcement learning algorithms can provide a basis for the modeling of agents dexterous strategies.

Recommended Citation

Bi, Zeng; Xiao, Fang; Kong, Deshuai; Song, Xiangxiang; Jia, Zhengxuan; and Lin, Tingyu (2022) "A Data-Driven Modeling Method for Game Adversity Agent," Journal of System Simulation: Vol. 33: Iss. 12, Article 8.
DOI: 10.16182/j.issn1004731x.joss.20-FZ0532
Available at: https://dc-china-simulation.researchcommons.org/journal/vol33/iss12/8

First Page

2838

Revised Date

2021-06-08

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.20-FZ0532

Last Page

2845

CLC

TP391.9

Recommended Citation

Zeng Bi, Fang Xiao, Kong Deshuai, Song Xiangxiang, Jia Zhengxuan, Lin Tingyu. A Data-Driven Modeling Method for Game Adversity Agent[J]. Journal of System Simulation, 2021, 33(12): 2838-2845.

DOI

10.16182/j.issn1004731x.joss.20-FZ0532