Evolution Strategy Performance on the Rastrigin Function
Evolutionary computation 2025 MIT
we are going to talk about Impact of Seed and Selection Mechanism.
today I will be presenting an analysis of Evolution Strategy performance on the Rastrigin function, specifically examining the impact of random seed and selection mechanism.
Optimisation problems, particularly those involving multi-modal functions such as the Rastrigin function, are inherently complex due to their numerous local minima. Evolution Strategies, a class of population-based metaheuristic algorithms, are well-suited to navigate such intricate landscapes. The primary objective of this presentation is to delineate an analysis of Evolution Strategy performance on the two-dimensional Rastrigin function, with a particular emphasis on discerning the influence of both the random seed and the chosen selection strategy—specifically, the (μ, λ) and (μ + λ) approaches. This investigation is pertinent for enhancing our comprehension of ES behaviour in stochastic environments.
Source code: git@github.com:Python-Neiva/COIT29224-EvolutionStrategy.git
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