Adaptive Combination of a Genetic Algorithm and Novelty Search for Deep Neuroevolution

Eyal Segal, Moshe Sipper

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Evolutionary Computation (EC) has been shown to be able to quickly train Deep Artificial Neural Networks (DNNs) to solve Reinforcement Learning (RL) problems. While a Genetic Algorithm (GA) is well-suited for exploiting reward functions that are neither deceptive nor sparse, it struggles when the reward function is either of those. To that end, Novelty Search (NS) has been shown to be able to outperform gradient-following optimizers in some cases, while under-performing in others. We propose a new algorithm: Explore-Exploit g- Adaptive Learner (E2gAL, or EyAL). By preserving a dynamically-sized niche of novelty-seeking agents, the algorithm manages to maintain population diversity, exploiting the reward signal when possible and exploring otherwise. The algorithm combines both the exploitation power of a GA and the exploration power of NS, while maintaining their simplicity and elegance. Our experiments show that EyAL outperforms NS in most scenarios, while being on par with a GA—and in some scenarios it can outperform both. EyAL also allows the substitution of the exploiting component (GA) and the exploring component (NS) with other algorithms, e.g., Evolution Strategy and Surprise Search, thus opening the door for future research.

Original languageEnglish
Title of host publicationProceedings of the 14th International Joint Conference on Computational Intelligence, IJCCI 2022
EditorsThomas Bäck, Janusz Kacprzyk, Niki van Stein, Christian Wagner, Jonathan Garibaldi, H.K. Lam, Marie Cottrell, Faiyaz Doctor, Joaquim Filipe, Kevin Warwick
PublisherScience and Technology Publications, Lda
Pages143-150
Number of pages8
ISBN (Print)9789897586118
DOIs
StatePublished - 1 Jan 2022
Event14th International Joint Conference on Computational Intelligence, IJCCI 2022 - Valletta, Malta
Duration: 24 Oct 202226 Oct 2022

Publication series

NameInternational Joint Conference on Computational Intelligence
Volume1
ISSN (Electronic)2184-3236

Conference

Conference14th International Joint Conference on Computational Intelligence, IJCCI 2022
Country/TerritoryMalta
CityValletta
Period24/10/2226/10/22

Keywords

  • Evolutionary Computation
  • Genetic Algorithm
  • Novelty Search
  • Reinforcement Learning

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computational Theory and Mathematics

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