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

18 December 2017

Jeff Clune

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

50 / 276 papers shown

Title
Applications of the Free Energy Principle to Machine Learning and Neuroscience Beren Millidge DRL 22 7 0 30 Jun 2021
Deep Multiagent Reinforcement Learning: Challenges and Directions Annie Wong Thomas Bäck Anna V. Kononova Aske Plaat AI4CE 34 88 0 29 Jun 2021
Neuroevolution-Enhanced Multi-Objective Optimization for Mixed-Precision Quantization Santiago Miret Vui Seng Chua Mattias Marder Mariano Phielipp Nilesh Jain Somdeb Majumdar 23 8 0 14 Jun 2021
Black-box adversarial attacks using Evolution Strategies Hao Qiu Leonardo Lucio Custode Giovanni Iacca AAML 33 18 0 30 Apr 2021
MAGMA: An Optimization Framework for Mapping Multiple DNNs on Multiple Accelerator Cores Sheng-Chun Kao T. Krishna 24 50 0 28 Apr 2021
Policy Manifold Search: Exploring the Manifold Hypothesis for Diversity-based Neuroevolution Nemanja Rakićević Antoine Cully Petar Kormushev 9 34 0 27 Apr 2021
ALF -- A Fitness-Based Artificial Life Form for Evolving Large-Scale Neural Networks Rune Krauss M. Merten Mirco Bockholt R. Drechsler 16 1 0 16 Apr 2021
A coevolutionary approach to deep multi-agent reinforcement learning Daan Klijn A. E. Eiben 16 8 0 12 Apr 2021
Selection-Expansion: A Unifying Framework for Motion-Planning and Diversity Search Algorithms Alexandre Chenu Nicolas Perrin-Gilbert Stéphane Doncieux Olivier Sigaud 12 1 0 10 Apr 2021
Quality Evolvability ES: Evolving Individuals With a Distribution of Well Performing and Diverse Offspring Adam Katona D. Franks James Alfred Walker 31 5 0 19 Mar 2021
Policy Search with Rare Significant Events: Choosing the Right Partner to Cooperate with Paul Ecoffet Nicolas Fontbonne Jean-Baptiste André Nicolas Bredèche 8 3 0 11 Mar 2021
Meta Learning Black-Box Population-Based Optimizers H. Gomes B. Léger Christian Gagné 42 13 0 05 Mar 2021
Neuroevolution in Deep Learning: The Role of Neutrality E. López 16 4 0 16 Feb 2021
Diverse Auto-Curriculum is Critical for Successful Real-World Multiagent Learning Systems Yaodong Yang Jun Luo Ying Wen Oliver Slumbers D. Graves H. Ammar Jun Wang Matthew E. Taylor 21 35 0 15 Feb 2021
Derivative-Free Reinforcement Learning: A Review Hong Qian Yang Yu OffRL 23 42 0 10 Feb 2021
Regenerating Soft Robots through Neural Cellular Automata Kazuya Horibe Kathryn Walker S. Risi 21 27 0 04 Feb 2021
ES-ENAS: Efficient Evolutionary Optimization for Large Hybrid Search Spaces Xingyou Song K. Choromanski Jack Parker-Holder Yunhao Tang Qiuyi Zhang ... Deepali Jain Wenbo Gao Aldo Pacchiano Tamás Sarlós Yuxiang Yang 19 0 0 19 Jan 2021
Interpretable discovery of new semiconductors with machine learning Hitarth Choubisa Petar Todorović Joao M. Pina D. Parmar Ziliang Li Oleksandr Voznyy Isaac Tamblyn E. Sciences 23 11 0 12 Jan 2021
Advances in Electron Microscopy with Deep Learning Jeffrey M. Ede 35 2 0 04 Jan 2021
Evolving the Behavior of Machines: From Micro to Macroevolution Jean-Baptiste Mouret AI4CE 11 13 0 21 Dec 2020
Policy Manifold Search for Improving Diversity-based Neuroevolution Nemanja Rakićević Antoine Cully Petar Kormushev 27 0 0 15 Dec 2020
An Efficient Asynchronous Method for Integrating Evolutionary and Gradient-based Policy Search Kyunghyun Lee Byeong-uk Lee Ukcheol Shin In So Kweon 30 22 0 10 Dec 2020
A multi-agent evolutionary robotics framework to train spiking neural networks Souvik Das Anirudh Shankar Vaneet Aggarwal 19 1 0 07 Dec 2020
General Characterization of Agents by States they Visit Anssi Kanervisto Tomi Kinnunen Ville Hautamaki 12 3 0 02 Dec 2020
Assessing and Accelerating Coverage in Deep Reinforcement Learning Arpan Kusari 12 2 0 01 Dec 2020
Reward Conditioned Neural Movement Primitives for Population Based Variational Policy Optimization M. Akbulut Utku Bozdoğan Ahmet E. Tekden Emre Ugur 21 5 0 09 Nov 2020
Machine versus Human Attention in Deep Reinforcement Learning Tasks Sihang Guo Ruohan Zhang Bo Liu Yifeng Zhu M. Hayhoe D. Ballard Peter Stone OffRL 24 25 0 29 Oct 2020
Learning Guidance Rewards with Trajectory-space Smoothing Tanmay Gangwani Yuanshuo Zhou Jian Peng 26 33 0 23 Oct 2020
Competitiveness of MAP-Elites against Proximal Policy Optimization on locomotion tasks in deterministic simulations Szymon Brych Antoine Cully 8 4 0 17 Sep 2020
Evolutionary Selective Imitation: Interpretable Agents by Imitation Learning Without a Demonstrator Roy Eliya J. Herrmann 14 2 0 17 Sep 2020
Review: Deep Learning in Electron Microscopy Jeffrey M. Ede 36 79 0 17 Sep 2020
RECOApy: Data recording, pre-processing and phonetic transcription for end-to-end speech-based applications Adriana Stan 31 5 0 11 Sep 2020
Sample-Efficient Automated Deep Reinforcement Learning Jörg Franke Gregor Koehler André Biedenkapp Frank Hutter 31 39 0 03 Sep 2020
CLAN: Continuous Learning using Asynchronous Neuroevolution on Commodity Edge Devices Parth Mannan A. Samajdar T. Krishna 31 2 0 27 Aug 2020
Correspondence between neuroevolution and gradient descent S. Whitelam V. Selin Sang-Won Park Isaac Tamblyn 17 18 0 15 Aug 2020
Lights and Shadows in Evolutionary Deep Learning: Taxonomy, Critical Methodological Analysis, Cases of Study, Learned Lessons, Recommendations and Challenges Aritz D. Martinez Javier Del Ser Esther Villar-Rodriguez E. Osaba Javier Poyatos Siham Tabik Daniel Molina Francisco Herrera 35 26 0 09 Aug 2020
Hierarchical Deep Reinforcement Learning Approach for Multi-Objective Scheduling With Varying Queue Sizes Yoni Birman Ziv Ido Gilad Katz A. Shabtai 23 3 0 17 Jul 2020
OccamNet: A Fast Neural Model for Symbolic Regression at Scale Owen Dugan Rumen Dangovski Allan dos Santos Costa Samuel Kim Pawan Goyal J. Jacobson M. Soljavcić 26 11 0 16 Jul 2020
Application of Neuroevolution in Autonomous Cars G. Sainath S. Vignesh S. Siddarth G. Suganya 11 6 0 26 Jun 2020
An adaptive stochastic gradient-free approach for high-dimensional blackbox optimization Anton Dereventsov Clayton Webster Joseph Daws 22 10 0 18 Jun 2020
Neuroevolution in Deep Neural Networks: Current Trends and Future Challenges E. Galván P. Mooney 27 129 0 09 Jun 2020
Generative Design of Hardware-aware DNNs Sheng-Chun Kao Arun Ramamurthy T. Krishna MQ 19 2 0 06 Jun 2020
The Adversarial Resilience Learning Architecture for AI-based Modelling, Exploration, and Operation of Complex Cyber-Physical Systems Eric M. S. P. Veith Nils Wenninghoff Emilie Frost 18 5 0 27 May 2020
Visual Analytics and Human Involvement in Machine Learning Salomon Eisler Joachim Meyer 11 6 0 12 May 2020
RSO: A Gradient Free Sampling Based Approach For Training Deep Neural Networks Rohun Tripathi Bharat Singh 14 5 0 12 May 2020
Smooth Exploration for Robotic Reinforcement Learning Antonin Raffin Jens Kober F. Stulp 32 57 0 12 May 2020
Accelerating Deep Neuroevolution on Distributed FPGAs for Reinforcement Learning Problems Alexis Asseman Nicolas Antoine A. Ozcan 24 4 0 10 May 2020
Safe Reinforcement Learning through Meta-learned Instincts Djordje Grbic S. Risi 18 7 0 06 May 2020
Generating and Adapting to Diverse Ad-Hoc Cooperation Agents in Hanabi Rodrigo Canaan Xianbo Gao Julian Togelius Andy Nealen Stefan Menzel 12 11 0 28 Apr 2020
First return, then explore Adrien Ecoffet Joost Huizinga Joel Lehman Kenneth O. Stanley Jeff Clune 47 350 0 27 Apr 2020