CMA-ES,.

Russell M Martin1, Steven H Collins2

  • 1Department of Mechanical Engineering, Stanford University, Stanford, 94305, USA rumartin@stanford.edu.

Evolutionary computation
|January 28, 2026
PubMed
概括

与标准方法相比,自适应采样CMA-ES (AS-CMA) 通过动态分配评估时间,提高速度和降低成本来优化机器人政策. 这种新的方法提高了噪音环境中的效率,设置的复杂性最小.

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