Why Greatness Cannot Be Planned: The Myth of the Objective
Joel Lehman , Kenneth O. Stanley
41
2015
Evolving policy geometry for scalable multiagent learning
Sebastian Risi , David B. D'Ambrosio , Joel Lehman , Kenneth O. Stanley
adaptive agents and multi-agents systems 731 -738
46
2010
Exploiting Open-Endedness to Solve Problems Through the Search for Novelty
Joel Lehman , Kenneth O. Stanley
Artificial Life 329 -336
358
2008
EVOLUTION THROUGH THE SEARCH FOR NOVELTY
Joel Lehman
16
2012
Combining search-based procedural content generation and social gaming in the Petalz video game
Sebastian Risi , David B. D'Ambrosio , Joel Lehman , Kenneth O. Stanley
national conference on artificial intelligence 63 -68
48
2012
Using Indirect Encoding of Multiple Brains to Produce Multimodal Behavior
Sebastian Risi , Jacob Schrum , Joel Lehman
arXiv: Artificial Intelligence
7
2016
Creative Generation of 3D Objects with Deep Learning and Innovation Engines.
Sebastian Risi , Jeff Clune , Joel Lehman
ICCC 180 -187
53
2016
Deep Neuroevolution: Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning
Jeff Clune , Joel Lehman , Kenneth O. Stanley , Felipe Petroski Such
arXiv: Neural and Evolutionary Computing
712
2017
Safe Mutations for Deep and Recurrent Neural Networks through Output Gradients
Jeff Clune , Joel Lehman , Kenneth O. Stanley , Jay Chen
arXiv: Neural and Evolutionary Computing
85
2017
An Intriguing Failing of Convolutional Neural Networks and the CoordConv Solution
Piero Molino , Joel Lehman , Jason Yosinski , Felipe Petroski Such
arXiv: Computer Vision and Pattern Recognition
667
2018
An Atari Model Zoo for Analyzing, Visualizing, and Comparing Deep Reinforcement Learning Agents
Jeff Clune , Joel Lehman , Marc G. Bellemare , Pablo Samuel Castro
arXiv: Neural and Evolutionary Computing
51
2018
Paired Open-Ended Trailblazer (POET): Endlessly Generating Increasingly Complex and Diverse Learning Environments and Their Solutions
Jeff Clune , Joel Lehman , Kenneth O. Stanley , Rui Wang
arXiv: Neural and Evolutionary Computing
169
2019
Go-Explore: a New Approach for Hard-Exploration Problems
Jeff Clune , Joel Lehman , Kenneth O. Stanley , Joost Huizinga
arXiv: Learning
333
2019
Learning Belief Representations for Imitation Learning in POMDPs
Jian Peng , Joel Lehman , Tanmay Gangwani , Qiang Liu
arXiv: Learning
24
2019
Evolvability ES: Scalable and Direct Optimization of Evolvability
Jeff Clune , Joel Lehman , Kenneth O. Stanley , Alexander Gajewski
arXiv: Neural and Evolutionary Computing
20
2019
Improving Exploration in Evolution Strategies for Deep Reinforcement Learning via a Population of Novelty-Seeking Agents
Jeff Clune , Joel Lehman , Kenneth O. Stanley , Felipe Petroski Such
neural information processing systems 31 5027 -5038
333
2018
Towards Empathic Deep Q-Learning
Joel Lehman , Jacqueline Heinerman , Bart Bussmann
international joint conference on artificial intelligence 1 -7
7
2019
Learning to Continually Learn
Thomas Miconi , Jeff Clune , Joel Lehman , Kenneth O. Stanley
arXiv: Learning
121
2020
Reinforcement Learning Under Moral Uncertainty
Joel Lehman , Adrien Ecoffet
arXiv: Artificial Intelligence
17
2020
Enhanced POET: Open-ended Reinforcement Learning through Unbounded Invention of Learning Challenges and their Solutions
Jeffrey Clune , Joel Lehman , Kenneth Stanley , Aditya Rawal
international conference on machine learning 1 9940 -9951
64
2020