Adaptability of Improved NEAT in Variable Environments
preprintposted on 25.10.2021, 21:06 by Crewe BaileyCrewe Bailey
Qualitative research experiment to gather descriptive data on the NEAT algorithm’s performance in an environment with variability. Individual research performed for my AP Research paper. The experiment was conducted using Python and the NEAT-Python library. The research conducted was for the sake of doing research in the field of AI in computer science and is rather outdated.
Email Address of Submitting Author160236b@acadiau.ca
Submitting Author's InstitutionAcadia University
Submitting Author's CountryCanada
Artificial Intelligence (AI)Machine Learning (ML)Genetic Algorithm (GA)Evolutionary AlgorithmNeuroevolutionNeural Network (NN)AdaptabilityFitnessVariable EnvironmentEvolutionary ProgrammingSpeciationIncreasing Population SizeAutomatic Feature SelectionRecurrent ConnectionsRecurrent Neural Network (RNN)