Joost Huizinga

Research Scientist at OpenAI
Photo of six-legged robot Publications
These are my publications:
Scaling MAP-Elites to Deep Neuroevolution
Colas C, Huizinga J, Madhavan V, Clune J (2020) Scaling MAP-Elites to Deep Neuroevolution. arXiv 1807.03392. (arXiv)
Guiding Neuroevolution with Structural Objectives
Ellefsen KO, Huizinga J, Torresen J (2020) Guiding Neuroevolution with Structural Objectives. arXiv 1807.03392. (Evolutionary computation)
Exploration Based Language Learning for Text-Based Games
Madotto A, Namazifar M, Huizinga J, Molino P, Ecoffet A, Zheng H, Papangelis A, Yu D, Khatri C, Tur G (2020) Exploration Based Language Learning for Text-Based Games. arXiv 2001.08868. (arXiv)
Go-explore: a new approach for hard-exploration problems
Ecoffet A, Huizinga J, Lehman J, Stanley KO, Clune J (2019) Go-explore: a new approach for hard-exploration problems. arXiv 1901.10995. (arXiv)
The Emergence of Canalization and Evolvability in an Open-Ended, Interactive Evolutionary System.
Huizinga J, Stanley K, Clune J (2018) The Emergence of Canalization and Evolvability in an Open-Ended, Interactive Evolutionary System. Artificial life 24 (3), 157-181. (Artificial life)
Evolving Multimodal Robot Behavior via Many Stepping Stones with the Combinatorial Multi-Objective Evolutionary Algorithm
Huizinga J, Clune J (2018) Evolving Multimodal Robot Behavior via Many Stepping Stones with the Combinatorial Multi-Objective Evolutionary Algorithm. arXiv 1807.03392. (arXiv)
Does aligning phenotypic and genotypic modularity improve the evolution of neural networks?
Huizinga J, Mouret JB, Clune J (2016) Does aligning phenotypic and genotypic modularity improve the evolution of neural networks? Proceedings of the Genetic and Evolutionary Computation Conference. (GECCO)
The evolutionary origins of hierarchy
Mengistu H, Huizinga J, Mouret JB, Clune J (2016) The evolutionary origins of hierarchy. PLoS computational biology 12 (6), e1004829. (PLoS computational biolog)
Evolving Neural Networks That Are Both Modular and Regular: HyperNeat Plus the Connection Cost Technique
Huizinga J, Mouret JB, Clune J (2014) Evolving Neural Networks That Are Both Modular and Regular: HyperNeat Plus the Connection Cost Technique. Proceedings of the Genetic and Evolutionary Computation Conference. 697-704. (GECCO)