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Joel Lehman — most-cited papers & profile · Reinforcement Learning
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Joel Lehman
7
papers ·
933
citations
Google Scholar ↗
Semantic Scholar ↗
OpenAlex ↗
Most-cited papers
Deep Neuroevolution: Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning
2017 · 558 citations
Go-Explore: a New Approach for Hard-Exploration Problems
2019 · 228 citations
Improving Exploration in Evolution Strategies for Deep Reinforcement Learning via a Population of Novelty-Seeking Agents
2017 · 116 citations
Learning Belief Representations for Imitation Learning in POMDPs
2019 · 13 citations
Reinforcement Learning Under Moral Uncertainty
2020 · 11 citations
Quality Diversity through Human Feedback: Towards Open-Ended Diversity-Driven Optimization
2023 · 5 citations
Towards Empathic Deep Q-Learning
2019 · 2 citations
Top co-authors
Jeff Clune
· 4
Kenneth O. Stanley
· 3
Adrien Ecoffet
· 2
Edoardo Conti
· 2
Felipe Petroski Such
· 2
Vashisht Madhavan
· 2
Bart Bussmann
· 1
Jacqueline Heinerman
· 1
Jenny Zhang
· 1
Jian Peng
· 1
Joost Huizinga
· 1
Lee Spector
· 1
Topics
Exploration
Policy Gradient
Value-Based
Model-Based RL
Multi-Agent
Game AI
Safe RL
RLHF & Alignment
Offline RL