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Lamarckian and Lifelong Memetic Search in Agent-Based Computing

机译:基于Agent的Lamarckian和终生模因搜索

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Memetic algorithms when used with care can help in balancing exploitation and exploration of the metaheuristics, without the overhead measured by the rapidly increased number of function fitness calls. The paper tackles such balancing of use of metaheuristics in an agent-oriented setting. In particular, application of local search during a computing agent's life is researched. The results shown for selected benchmark functions are presented along with necessary statistic testing.
机译:当谨慎使用模因算法时,可以帮助平衡元启发式方法的开发和探索,而不会因功能适应性调用的数量迅速增加而产生开销。本文致力于在面向代理的环境中平衡使用元启发式方法。特别是,研究了在计算代理程序生命周期内本地搜索的应用。给出了所选基准功能显示的结果以及必要的统计测试。

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