Neuroevolution, or neuro-evolution, is a form of machine learning that uses evolutionary algorithms to train artificial neural networks. It is most commonly applied in artificial life, computer games, and evolutionary robotics. A main benefit is that neuroevolution can be applied more widely than supervised learning algorithms, which require a syllabus of correct input-output pairs. In contrast, neuroevolution requires only a measure of a network's performance at a task. For example, the outcome of a game (i.e. whether one player won or lost) can be easily measured without providing labeled examples of desired strategies.
This library has been greatly influenced by xviniette. My motivation was to rewrite it in TypeScript.
import * as Neuroevolution from './node_modules/neuroevolution-typescript/main';
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This project is licensed under the MIT License - see the LICENSE.md file for details.