A Heuristic Fast Task Allocation Algorithm for War Game Simulation Scenarios
Tianhao Wang, Zhentao Guo, Licheng Sun, Ao Ding, Ying Jin, Hongbin Ma
- 发表年份
- 2025
- 引用次数
- 1
摘要
Wargame simulations often involve complex battlefield scenarios with various tasks such as reconnaissance, attack, and support, each with different urgency levels and priorities. Effective task allocation requires considering task urgency, robot capabilities, and inter-task relationships to ensure critical tasks are addressed promptly. In this paper, a heuristic fast task assignment algorithm for war game simulation scenarios is proposed. The approach considers various factors, such as task urgency, robot capabilities, and spatial constraints, to ensure a balanced and timely execution of tasks. By applying a heuristic search strategy, the algorithm significantly reduces the computational complexity compared to traditional methods, while maintaining high-quality solutions. Experimental results demonstrate the effectiveness of the proposed algorithm in terms of task completion time, load balancing, and overall system performance in war game simulations.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991