TAO ZHANG

TAO ZHANG

Ph.D. student at McGill University

Publications

Toward Rapid and Optimal Strategy for Swarm Conflict: A Computational Game Approach

Accepted by IEEE Transactions on Aerospace and Electronic Systems</i>, 2024

Authors: Tao Zhang*, Yiji Zhu, Dongying Ma, Xiaodong Wang, Chaoyong Li

The decision and control problem for swarm operations is crucial for autonomous management of military conflict. In this paper, we prove that the underlying decision and control problem can be treated as a noncooperative game problem, and then proceed to introduce a parallelized algorithm to seek the desired Nash equilibrium with the help of the maximum weight matching algorithm. The proposed scheme is proved to be optimal with a guaranteed -Nash solution and rapid computational speed.

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An Optimal Task Management and Control Scheme for Military Operations with Dynamic Game Strategy

Published in Aerospace Science and Technology, 2021

Authors: Tao Zhang*, Chengchao Li, Dongying Ma, Xiaodong Wang, Chaoyong Li.

As is well known, military operation in a combat scenario is extremely intricate and often prone to optimal and real-time decisions. In this paper, we study task management and control problem for military operations with a dynamic game strategy. Toward this, the underlying problem is modeled by a matrix game scheme with performance index defined for both parties. Then, we proceed to present a fast and optimal search algorithm, inspired by graph theory and Kuhn-Munkres algorithm, to solve dimension explosion problem inherent with matrix game scheme and retrieve the optimal solution for each combat entity.

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