ESA combines two areas of RL and evolutionary algo- rithm. It regards the optimization algorithm as an agent for executing optimization tasks, as shown in Fig. 1, performs sampling actions by analyzing the current state, and learns from the feedback of sampling to improve the agent's decision- making ability.
May 24, 2022 · This article introduces a novel optimization framework to solve costly optimization problems, called the evolutionary sampling agent (ESA). ESA ...
This article introduces a novel optimization framework to solve costly optimization problems, called the evolutionary sampling agent (ESA). ESA considers the ...
This paper introduces a novel optimization framework to solve costly optimization problems, called evolutionary sampling agent (ESA). ESA considers the ...
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This paper proposes a composite surrogate-assisted evolutionary algorithm for expensive many-objective optimization.
Further, to improve the ability to search with a limited RFE budget, Zhen et al. designed an evolutionary sampling agent (ESA) to solve expensive problems [24] ...
Mar 20, 2024 · This paper provides a comprehensive survey of these evolutionary algorithms for HEPs. We start with a brief introduction to the research status and the basic ...
Jun 17, 2021 · This paper introduces a novel optimization framework to solve costly optimization problems, called evolutionary sampling agent (ESA). ESA ...
Data-driven evolutionary sampling optimization for expensive problems, zhenhuixiang/DESO code.zip. ESA, Evolutionary Sampling Agent for Expensive Problems ...
May 18, 2024 · This paper conducts a comprehensive survey on SAEAs tailored to address ECOPs. This survey comprises two primary segments.