Evolutionary Strategy (ES) is an optimization algorithm inspired by the process of natural evolution, where a population of candidate solutions evolves over generations to improve performance on a given task. It emphasizes mutation and selection mechanisms, often using a population-based approach to explore complex search spaces and discover optimal or near-optimal solutions.

Evolutionary Strategy

An optimization algorithm is a method or procedure used to find the best solution to a problem by minimizing or maximizing a particular function. These algorithms are fundamental in various fields, including machine learning, operations research, and engineering, where they help in efficiently navigating complex solution spaces to achieve optimal outcomes.

Optimization Algorithm

Natural evolution is the process by which populations of organisms change over generations through mechanisms such as natural selection, mutation, and genetic drift, leading to the diversity of life forms observed today. It is a fundamental concept in biology that explains how complex traits and species arise and adapt in response to environmental pressures.

Natural Evolution

Population of candidate solutions

Generations

Performance improvement is a systematic process aimed at enhancing the efficiency and effectiveness of an organization or individual by identifying performance gaps and implementing strategies to close them. It involves continuous assessment, feedback, and adaptation to achieve optimal results and sustain long-term success.

Concepts

Relevant Degrees

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