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Ideas for Improving the Field of Machine Learning: Summarizing Discussion from the NeurIPS 2019 Retrospectives Workshop

Jul 21, 2020
Shagun Sodhani, Mayoore S. Jaiswal, Lauren Baker, Koustuv Sinha, Carl Shneider, Peter Henderson, Joel Lehman, Ryan Lowe


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Open Questions in Creating Safe Open-ended AI: Tensions Between Control and Creativity

Jun 12, 2020
Adrien Ecoffet, Jeff Clune, Joel Lehman


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Reinforcement Learning Under Moral Uncertainty

Jun 08, 2020
Adrien Ecoffet, Joel Lehman

* 33 pages, 17 figures 

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Synthetic Petri Dish: A Novel Surrogate Model for Rapid Architecture Search

May 27, 2020
Aditya Rawal, Joel Lehman, Felipe Petroski Such, Jeff Clune, Kenneth O. Stanley


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First return then explore

May 14, 2020
Adrien Ecoffet, Joost Huizinga, Joel Lehman, Kenneth O. Stanley, Jeff Clune

* 45 pages, 13 figures, 4 tables; reorganized sections and modified SI text extensively 

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Enhanced POET: Open-Ended Reinforcement Learning through Unbounded Invention of Learning Challenges and their Solutions

Apr 13, 2020
Rui Wang, Joel Lehman, Aditya Rawal, Jiale Zhi, Yulun Li, Jeff Clune, Kenneth O. Stanley

* 23 pages, 14 figures 

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Learning to Continually Learn

Mar 04, 2020
Shawn Beaulieu, Lapo Frati, Thomas Miconi, Joel Lehman, Kenneth O. Stanley, Jeff Clune, Nick Cheney


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Generative Teaching Networks: Accelerating Neural Architecture Search by Learning to Generate Synthetic Training Data

Dec 17, 2019
Felipe Petroski Such, Aditya Rawal, Joel Lehman, Kenneth O. Stanley, Jeff Clune


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Evolvability ES: Scalable and Direct Optimization of Evolvability

Jul 13, 2019
Alexander Gajewski, Jeff Clune, Kenneth O. Stanley, Joel Lehman

* Published in GECCO 2019 

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Towards Empathic Deep Q-Learning

Jun 26, 2019
Bart Bussmann, Jacqueline Heinerman, Joel Lehman

* To be presented as a poster at the IJCAI-19 AI Safety Workshop 

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Evolutionary Computation and AI Safety: Research Problems Impeding Routine and Safe Real-world Application of Evolution

Jun 24, 2019
Joel Lehman


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Learning Belief Representations for Imitation Learning in POMDPs

Jun 22, 2019
Tanmay Gangwani, Joel Lehman, Qiang Liu, Jian Peng

* Conference on Uncertainty in Artificial Intelligence (UAI 2019) 

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Go-Explore: a New Approach for Hard-Exploration Problems

Jan 30, 2019
Adrien Ecoffet, Joost Huizinga, Joel Lehman, Kenneth O. Stanley, Jeff Clune

* 37 pages, 14 figures 

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Paired Open-Ended Trailblazer (POET): Endlessly Generating Increasingly Complex and Diverse Learning Environments and Their Solutions

Jan 09, 2019
Rui Wang, Joel Lehman, Jeff Clune, Kenneth O. Stanley

* 27 pages, 8 figures 

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An Atari Model Zoo for Analyzing, Visualizing, and Comparing Deep Reinforcement Learning Agents

Dec 17, 2018
Felipe Petroski Such, Vashisht Madhavan, Rosanne Liu, Rui Wang, Pablo Samuel Castro, Yulun Li, Ludwig Schubert, Marc Bellemare, Jeff Clune, Joel Lehman


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Improving Exploration in Evolution Strategies for Deep Reinforcement Learning via a Population of Novelty-Seeking Agents

Oct 29, 2018
Edoardo Conti, Vashisht Madhavan, Felipe Petroski Such, Joel Lehman, Kenneth O. Stanley, Jeff Clune


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The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities

Aug 14, 2018
Joel Lehman, Jeff Clune, Dusan Misevic, Christoph Adami, Lee Altenberg, Julie Beaulieu, Peter J. Bentley, Samuel Bernard, Guillaume Beslon, David M. Bryson, Patryk Chrabaszcz, Nick Cheney, Antoine Cully, Stephane Doncieux, Fred C. Dyer, Kai Olav Ellefsen, Robert Feldt, Stephan Fischer, Stephanie Forrest, Antoine Frénoy, Christian Gagné, Leni Le Goff, Laura M. Grabowski, Babak Hodjat, Frank Hutter, Laurent Keller, Carole Knibbe, Peter Krcah, Richard E. Lenski, Hod Lipson, Robert MacCurdy, Carlos Maestre, Risto Miikkulainen, Sara Mitri, David E. Moriarty, Jean-Baptiste Mouret, Anh Nguyen, Charles Ofria, Marc Parizeau, David Parsons, Robert T. Pennock, William F. Punch, Thomas S. Ray, Marc Schoenauer, Eric Shulte, Karl Sims, Kenneth O. Stanley, François Taddei, Danesh Tarapore, Simon Thibault, Westley Weimer, Richard Watson, Jason Yosinski


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An Intriguing Failing of Convolutional Neural Networks and the CoordConv Solution

Jul 09, 2018
Rosanne Liu, Joel Lehman, Piero Molino, Felipe Petroski Such, Eric Frank, Alex Sergeev, Jason Yosinski


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ES Is More Than Just a Traditional Finite-Difference Approximator

May 01, 2018
Joel Lehman, Jay Chen, Jeff Clune, Kenneth O. Stanley


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Safe Mutations for Deep and Recurrent Neural Networks through Output Gradients

May 01, 2018
Joel Lehman, Jay Chen, Jeff Clune, Kenneth O. Stanley


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Deep Neuroevolution: Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning

Apr 20, 2018
Felipe Petroski Such, Vashisht Madhavan, Edoardo Conti, Joel Lehman, Kenneth O. Stanley, Jeff Clune


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Using Indirect Encoding of Multiple Brains to Produce Multimodal Behavior

Apr 26, 2016
Jacob Schrum, Joel Lehman, Sebastian Risi


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Evolvability Is Inevitable: Increasing Evolvability Without the Pressure to Adapt

Feb 05, 2013
Joel Lehman, Kenneth O. Stanley


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