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

18 December 2017

Jeff Clune

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

26 / 76 papers shown

Title
AutoPhase: Juggling HLS Phase Orderings in Random Forests with Deep Reinforcement Learning Qijing Huang Ameer Haj-Ali William S. Moses J. Xiang Ion Stoica Krste Asanović J. Wawrzynek 21 56 0 02 Mar 2020
Simultaneously Evolving Deep Reinforcement Learning Models using Multifactorial Optimization Aritz D. Martinez E. Osaba Javier Del Ser Francisco Herrera 22 10 0 25 Feb 2020
Effective Diversity in Population Based Reinforcement Learning Jack Parker-Holder Aldo Pacchiano K. Choromanski Stephen J. Roberts 22 158 0 03 Feb 2020
Population-Guided Parallel Policy Search for Reinforcement Learning Whiyoung Jung Giseung Park Y. Sung OffRL 24 38 0 09 Jan 2020
Covariance Matrix Adaptation for the Rapid Illumination of Behavior Space Matthew C. Fontaine Julian Togelius Stefanos Nikolaidis Amy K. Hoover 48 134 0 05 Dec 2019
Efficient Novelty-Driven Neural Architecture Search Miao Zhang Huiqi Li Shirui Pan Taoping Liu Steven W. Su 28 1 0 22 Jul 2019
Learning to Score Behaviors for Guided Policy Optimization Aldo Pacchiano Jack Parker-Holder Yunhao Tang A. Choromańska K. Choromanski Michael I. Jordan 27 38 0 11 Jun 2019
AI-GAs: AI-generating algorithms, an alternate paradigm for producing general artificial intelligence Jeff Clune 17 116 0 27 May 2019
Go-Explore: a New Approach for Hard-Exploration Problems Adrien Ecoffet Joost Huizinga Joel Lehman Kenneth O. Stanley Jeff Clune AI4TS 24 363 0 30 Jan 2019
Malthusian Reinforcement Learning Joel Z Leibo Julien Perolat Edward Hughes S. Wheelwright Adam H. Marblestone Edgar A. Duénez-Guzmán P. Sunehag Iain Dunning T. Graepel AI4CE 33 37 0 17 Dec 2018
PNS: Population-Guided Novelty Search for Reinforcement Learning in Hard Exploration Environments Qihao Liu Yujia Wang Xiao-Fei Liu 25 8 0 26 Nov 2018
Evolving intrinsic motivations for altruistic behavior Jane X. Wang Edward Hughes Chrisantha Fernando Wojciech M. Czarnecki Edgar A. Duénez-Guzmán Joel Z Leibo 27 75 0 14 Nov 2018
EA-LSTM: Evolutionary Attention-based LSTM for Time Series Prediction Youru Li Zhenfeng Zhu Deqiang Kong Jinhyuk Lee Yao Zhao AI4TS 33 355 0 09 Nov 2018
Transfer Learning versus Multi-agent Learning regarding Distributed Decision-Making in Highway Traffic Mark Schutera Niklas Goby Dirk Neumann Markus Reischl 21 5 0 19 Oct 2018
Episodic Curiosity through Reachability Nikolay Savinov Anton Raichuk Raphaël Marinier Damien Vincent Marc Pollefeys Timothy Lillicrap Sylvain Gelly 17 267 0 04 Oct 2018
CEM-RL: Combining evolutionary and gradient-based methods for policy search Aloïs Pourchot Olivier Sigaud 32 160 0 02 Oct 2018
Importance mixing: Improving sample reuse in evolutionary policy search methods Aloïs Pourchot Nicolas Perrin Olivier Sigaud 15 14 0 17 Aug 2018
Curiosity Driven Exploration of Learned Disentangled Goal Spaces A. Laversanne-Finot Alexandre Péré Pierre-Yves Oudeyer DRL 27 87 0 04 Jul 2018
Learning Self-Imitating Diverse Policies Tanmay Gangwani Qiang Liu Jian Peng 29 65 0 25 May 2018
Discovering the Elite Hypervolume by Leveraging Interspecies Correlation Vassilis Vassiliades Jean-Baptiste Mouret 24 80 0 11 Apr 2018
Policy Search in Continuous Action Domains: an Overview Olivier Sigaud F. Stulp 16 72 0 13 Mar 2018
Back to Basics: Benchmarking Canonical Evolution Strategies for Playing Atari P. Chrabaszcz I. Loshchilov Frank Hutter 32 99 0 24 Feb 2018
Structured Control Nets for Deep Reinforcement Learning Mario Srouji Jian Zhang Ruslan Salakhutdinov 33 43 0 22 Feb 2018
State Representation Learning for Control: An Overview Timothée Lesort Natalia Díaz Rodríguez Jean-François Goudou David Filliat OffRL 30 319 0 12 Feb 2018
ES Is More Than Just a Traditional Finite-Difference Approximator Joel Lehman Jay Chen Jeff Clune Kenneth O. Stanley 25 89 0 18 Dec 2017
Deep Neuroevolution: Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning F. Such Vashisht Madhavan Edoardo Conti Joel Lehman Kenneth O. Stanley Jeff Clune 47 686 0 18 Dec 2017