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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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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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Fiber: A Platform for Efficient Development and Distributed Training for Reinforcement Learning and Population-Based Methods

Mar 25, 2020
Jiale Zhi, Rui Wang, Jeff Clune, Kenneth O. Stanley


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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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Scaling MAP-Elites to Deep Neuroevolution

Mar 03, 2020
CĂ©dric Colas, Joost Huizinga, Vashisht Madhavan, Jeff Clune

* 9 pages 

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Backpropamine: training self-modifying neural networks with differentiable neuromodulated plasticity

Feb 24, 2020
Thomas Miconi, Aditya Rawal, Jeff Clune, Kenneth O. Stanley

* 7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA, May 6-9, 2019 
* Presented at the 7th International Conference on Learning Representations (ICLR 2019) 

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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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A deep active learning system for species identification and counting in camera trap images

Oct 22, 2019
Mohammad Sadegh Norouzzadeh, Dan Morris, Sara Beery, Neel Joshi, Nebojsa Jojic, Jeff Clune

* 15 pages, 5 figures 

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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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AI-GAs: AI-generating algorithms, an alternate paradigm for producing general artificial intelligence

May 27, 2019
Jeff Clune


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Understanding Neural Networks via Feature Visualization: A survey

Apr 18, 2019
Anh Nguyen, Jason Yosinski, Jeff Clune

* A book chapter in an Interpretable ML book (http://www.interpretable-ml.org/book/

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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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Robustness to Out-of-Distribution Inputs via Task-Aware Generative Uncertainty

Dec 27, 2018
Rowan McAllister, Gregory Kahn, Jeff Clune, Sergey Levine


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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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Deep Curiosity Search: Intra-Life Exploration Can Improve Performance on Challenging Deep Reinforcement Learning Problems

Oct 22, 2018
Christopher Stanton, 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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Differentiable plasticity: training plastic neural networks with backpropagation

Jul 31, 2018
Thomas Miconi, Jeff Clune, Kenneth O. Stanley

* Proceedings of the 35th International Conference on Machine Learning (ICML2018), Stockholm, Sweden, PMLR 80, 2018 
* Presented at ICML 2018 

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Evolving Multimodal Robot Behavior via Many Stepping Stones with the Combinatorial Multi-Objective Evolutionary Algorithm

Jul 09, 2018
Joost Huizinga, Jeff Clune


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VINE: An Open Source Interactive Data Visualization Tool for Neuroevolution

May 03, 2018
Rui Wang, Jeff Clune, Kenneth O. Stanley


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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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On the Relationship Between the OpenAI Evolution Strategy and Stochastic Gradient Descent

Dec 18, 2017
Xingwen Zhang, Jeff Clune, Kenneth O. Stanley


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