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Computer-based strategy development in multi-agent systems using genetic algorithms.

机译:使用遗传算法在多主体系统中基于计算机的策略开发。

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The task of developing a strategy that generates highly adaptable and collaborative agents and produces optimum results can be an exhaustive process. Changes on the system environment conditions can make this task even more difficult. Using genetic algorithms to solve such tasks can be a reasonably fast and lightweight solution and offer a few advantages over traditional approaches that use Reinforcement Learning.; This work applied a genetic algorithm to a multi-agent system with the goal of examining techniques of strategy development applied to particular problems or goals common to a set of agents. The approach was experimented and the results showed that a genetic algorithm could generate an optimum result and overcome various optimization issues faced by other approaches.
机译:制定能够产生高度适应性和协作性代理并产生最佳结果的策略的任务可能是一个详尽的过程。系统环境条件的变化会使此任务更加困难。使用遗传算法来解决此类任务可能是一种相当快速且轻巧的解决方案,并且与使用强化学习的传统方法相比,具有一些优势。这项工作将遗传算法应用于多主体系统,目的是研究应用于特定问题或一组主体共有的目标的策略开发技术。对方法进行了实验,结果表明遗传算法可以产生最优结果,克服了其他方法面临的各种优化问题。

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