A Simulation of the Colonel Blotto Game using Genetic Algorithm

Document Type : Original Article


Department of Science and Technology Studies, AJA Command and Staff University, Tehran, Iran



Objective: The allocation of limited resources in the military field is an important challenge that seeks to maximize or minimize. Game theory is used to define resources in terms of conflict and definitions. One of the game theory research issues is Blato's Syringe game, which aims to allocate strategic resources.
Methodology: In this game, two players are given limited resources on a fixed number of battlefields, without knowledge of the opponent's decisions. In this article, this issue is solved by examining the genetic algorithm, which is a meta-heuristic algorithm.
Findings: On the other hand, by introducing the brute-force algorithm and solving all situations, a comparison has been made with the genetic algorithm in terms of execution time and optimality of resource allocation. According to the concluded data, the genetic algorithm works in this problem in 47% of the time similar to the brute-force algorithm and in 42% of the time it works better.
Conclusion: Using the Python programming language and the Django software framework, the Colonel Blato game simulator has been designed and implemented on the web platform, which includes user management pages, game creation, game list and game guide. This simulator has the ability to create problems and choose an opponent as another user, random allocation and genetic algorithm.


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