Redefining the Behavior Space for Multi-Objective MAP-Elites

Author:

Nickelson Anna1ORCID,Tumer Kagan1ORCID

Affiliation:

1. Collaborative Robotics and Intelligent Systems (CoRIS) Institute, Oregon State University, Corvallis, United States of America

Funder

NSF (National Science Foundation)

Publisher

ACM

Reference11 articles.

1. Lucas N. Alegre, Florian Felten, El-Ghazali Talbi, Grégoire Danoy, Ann Nowé, Ana L. C. Bazzan, and Bruno C. da Silva. 2022. MO-Gym: A Library of Multi-Objective Reinforcement Learning Environments. In Proceedings of the 34th Benelux Conference on Artificial Intelligence BNAIC/Benelearn 2022.

2. Benjamin Eysenbach, Abhishek Gupta, Julian Ibarz, and Sergey Levine. 2019. Diversity is All You Need: Learning Skills without a Reward Function. In International Conference on Learning Representations. https://openreview.net/forum?id=SJx63jRqFm

3. A practical guide to multi-objective reinforcement learning and planning

4. Joel Lehman and Kenneth O Stanley. 2011. Novelty search and the problem with objectives. Genetic programming theory and practice IX (2011), 37--56.

5. Jean-Baptiste Mouret and Jeff Clune. 2015. Illuminating search spaces by mapping elites. arXiv preprint arXiv:1504.04909 (2015). https://arxiv.org/abs/1504.04909

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