首页> 外文会议>AAAI Conference on Artificial Intelligence(AAAI-07); Innovative Applications of Artificial Intelligence Conference(IAAI-07); 20070722-26; 20070722-26; Vancouver(CA); Vancouver(CA) >Evolutionary and Lifetime Learning in Varying NK Fitness Landscape Changing Environments: An Analysis of both Fitness and Diversity
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Evolutionary and Lifetime Learning in Varying NK Fitness Landscape Changing Environments: An Analysis of both Fitness and Diversity

机译:NK健身景观变化环境中的进化和终生学习:健身和多样性的分析

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This paper examines the effects of lifetime learning on populations evolving genetically in a series of changing environments. The analysis of both fitness and diversity of the populations provides an insight into the improved performance provided by lifetime learning. The NK fitness landscape model is employed as the problem task, which has the advantage of being able to generate a variety of fitness landscapes of varying difficulty. Experiments observe the response of populations in an environment where problem difficulty increases and decreases with varying frequency. Results show that lifetime learning is capable of overall higher fitness levels and, in addition, that lifetime learning stimulates the diversity of the population. This increased diversity allows lifetime learning a greater level of recovery and stability than evolutionary learning alone.
机译:本文研究了终身学习对一系列不断变化的环境中遗传进化的种群的影响。人口适应性和多样性的分析提供了对终生学习所提供的改善的表现的洞察力。 NK健身景观模型用作问题任务,其优点是能够生成各种难度不同的健身景观。实验观察到在问题难度随频率变化而增加和减少的环境中,人口的反应。结果表明,终生学习能够提高整体健身水平,此外,终生学习可以刺激人口的多样性。这种增加的多样性使终生学习比单独的进化学习具有更高的恢复和稳定性。

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