Evolution Strategies as a Scalable Alternative to Reinforcement Learning

10 March 2017

Papers citing "Evolution Strategies as a Scalable Alternative to Reinforcement Learning"

50 / 407 papers shown

Title
Generative Evolutionary Strategy For Black-Box Optimizations C. Park 11 0 0 06 May 2022
Learning Discrete Structured Variational Auto-Encoder using Natural Evolution Strategies Alon Berliner Guy Rotman Yossi Adi Roi Reichart Tamir Hazan BDL DRL 24 4 0 03 May 2022
Exploration in Deep Reinforcement Learning: A Survey Pawel Ladosz Lilian Weng Minwoo Kim H. Oh OffRL 26 324 0 02 May 2022
TTOpt: A Maximum Volume Quantized Tensor Train-based Optimization and its Application to Reinforcement Learning Konstantin Sozykin Andrei Chertkov R. Schutski Anh-Huy Phan A. Cichocki Ivan Oseledets 14 35 0 30 Apr 2022
Watts: Infrastructure for Open-Ended Learning Aaron Dharna Charlie Summers Rohin Dasari Julian Togelius Amy K. Hoover 22 1 0 28 Apr 2022
HyperNCA: Growing Developmental Networks with Neural Cellular Automata Elias Najarro Shyam Sudhakaran Claire Glanois S. Risi 36 14 0 25 Apr 2022
Evolving Modular Soft Robots without Explicit Inter-Module Communication using Local Self-Attention F. Pigozzi Yujin Tang Eric Medvet David R Ha 44 22 0 13 Apr 2022
MetaCon: Unified Predictive Segments System with Trillion Concept Meta-Learning Keqian Li Yifan Hu Logan Palanisamy Lisa Jones A. Gupta J. E. Grigsby Ili Selinger Matt Gillingham Fei Tan 28 1 0 09 Mar 2022
Leveraging Randomized Smoothing for Optimal Control of Nonsmooth Dynamical Systems Quentin Le Lidec Fabian Schramm Louis Montaut Cordelia Schmid Ivan Laptev Justin Carpentier 38 24 0 08 Mar 2022
Leveraging Reward Gradients For Reinforcement Learning in Differentiable Physics Simulations Sean Gillen Katie Byl AI4CE 23 3 0 06 Mar 2022
Transfer Dynamics in Emergent Evolutionary Curricula Aaron Dharna Amy K. Hoover Julian Togelius Lisa Soros 27 6 0 03 Mar 2022
Exploring hyper-parameter spaces of neuroscience models on high performance computers with Learning to Learn Alper Yegenoglu Anand Subramoney T. Hater Cristian Jimenez-Romero W. Klijn Aarn Pérez Martín Michiel A. van der Vlag Michael Herty A. Morrison Sandra Díaz-Pier 29 7 0 28 Feb 2022
A Globally Convergent Evolutionary Strategy for Stochastic Constrained Optimization with Applications to Reinforcement Learning Youssef Diouane Aurelien Lucchi Vihang Patil 29 3 0 21 Feb 2022
MuZero with Self-competition for Rate Control in VP9 Video Compression Amol Mandhane A. Zhernov Maribeth Rauh Chenjie Gu Miaosen Wang ... Jackson Broshear Julian Schrittwieser Thomas Hubert Oriol Vinyals Timothy A. Mann 31 43 0 14 Feb 2022
Interpretable pipelines with evolutionarily optimized modules for RL tasks with visual inputs Leonardo Lucio Custode Giovanni Iacca 27 13 0 10 Feb 2022
Approximating Gradients for Differentiable Quality Diversity in Reinforcement Learning Bryon Tjanaka Matthew C. Fontaine Julian Togelius Stefanos Nikolaidis 38 50 0 08 Feb 2022
DiGamma: Domain-aware Genetic Algorithm for HW-Mapping Co-optimization for DNN Accelerators Sheng-Chun Kao Michael Pellauer A. Parashar T. Krishna 27 29 0 26 Jan 2022
Neural Circuit Architectural Priors for Embodied Control Nikhil X. Bhattasali A. Zador Tatiana A. Engel 88 5 0 13 Jan 2022
Direct Mutation and Crossover in Genetic Algorithms Applied to Reinforcement Learning Tasks Tarek Faycal Claudio Zito 9 2 0 13 Jan 2022
Black-Box Tuning for Language-Model-as-a-Service Tianxiang Sun Yunfan Shao Hong Qian Xuanjing Huang Xipeng Qiu VLM 50 256 0 10 Jan 2022
A Surrogate-Assisted Controller for Expensive Evolutionary Reinforcement Learning Yuxing Wang Tiantian Zhang Yongzhe Chang Bin Liang Xueqian Wang Bo Yuan 26 15 0 01 Jan 2022
Distributed Evolution Strategies Using TPUs for Meta-Learning Alex Sheng J. He 10 2 0 01 Jan 2022
Unbiased Gradient Estimation in Unrolled Computation Graphs with Persistent Evolution Strategies Paul Vicol Luke Metz Jascha Narain Sohl-Dickstein 27 68 0 27 Dec 2021
Parallelized and Randomized Adversarial Imitation Learning for Safety-Critical Self-Driving Vehicles Won Joon Yun Myungjae Shin Soyi Jung S. Kwon Joongheon Kim 22 5 0 26 Dec 2021
Automated Deep Learning: Neural Architecture Search Is Not the End Xuanyi Dong D. Kedziora Katarzyna Musial Bogdan Gabrys 29 26 0 16 Dec 2021
Godot Reinforcement Learning Agents E. Beeching Jilles Debangoye Olivier Simonin Christian Wolf GP OnRL 24 5 0 07 Dec 2021
NEORL: NeuroEvolution Optimization with Reinforcement Learning M. Radaideh Katelin Du Paul Seurin Devin Seyler Xubo Gu Haijiang Wang K. Shirvan OffRL 31 6 0 01 Dec 2021
Agent Spaces John C. Raisbeck M. W. Allen Hakho Lee 30 1 0 11 Nov 2021
Gradients are Not All You Need Luke Metz C. Freeman S. Schoenholz Tal Kachman 30 93 0 10 Nov 2021
Stable Lifelong Learning: Spiking neurons as a solution to instability in plastic neural networks Samuel Schmidgall Joe Hays 22 4 0 07 Nov 2021
Unifying Likelihood-free Inference with Black-box Optimization and Beyond Dinghuai Zhang Jie Fu Yoshua Bengio Aaron Courville 38 13 0 06 Oct 2021
Trustworthy AI: From Principles to Practices Bo-wen Li Peng Qi Bo Liu Shuai Di Jingen Liu Jiquan Pei Jinfeng Yi Bowen Zhou 119 356 0 04 Oct 2021
Guiding Evolutionary Strategies by Differentiable Robot Simulators Vladislav Kurenkov Bulat Maksudov 31 2 0 01 Oct 2021
Deep Reinforcement Learning Versus Evolution Strategies: A Comparative Survey Amjad Yousef Majid Serge Saaybi Tomas van Rietbergen Vincent François-Lavet R. V. Prasad Chris Verhoeven OffRL 62 55 0 28 Sep 2021
Curvature-Aware Derivative-Free Optimization Bumsu Kim HanQin Cai Daniel McKenzie W. Yin ODL 35 10 0 27 Sep 2021
Adaptive Sampling Quasi-Newton Methods for Zeroth-Order Stochastic Optimization Raghu Bollapragada Stefan M. Wild 35 11 0 24 Sep 2021
Introducing Symmetries to Black Box Meta Reinforcement Learning Louis Kirsch Sebastian Flennerhag Hado van Hasselt A. Friesen Junhyuk Oh Yutian Chen 22 30 0 22 Sep 2021
Reinforcement Learning with Evolutionary Trajectory Generator: A General Approach for Quadrupedal Locomotion Hao-bin Shi Bo Zhou Hongsheng Zeng Fan Wang Yueqiang Dong Jiangyong Li Kang Wang Hao Tian Max Q.-H. Meng 45 50 0 14 Sep 2021
Evolving Decomposed Plasticity Rules for Information-Bottlenecked Meta-Learning Fan Wang Hao Tian Haoyi Xiong Hua Wu Jie Fu Yang Cao Yu Kang Haifeng Wang AI4CE 15 3 0 08 Sep 2021
A Survey of Exploration Methods in Reinforcement Learning Susan Amin Maziar Gomrokchi Harsh Satija H. V. Hoof Doina Precup OffRL 32 80 0 01 Sep 2021
Deep Reinforcement Learning at the Edge of the Statistical Precipice Rishabh Agarwal Max Schwarzer Pablo Samuel Castro Aaron Courville Marc G. Bellemare OffRL 59 639 0 30 Aug 2021
Human-Level Reinforcement Learning through Theory-Based Modeling, Exploration, and Planning Pedro Tsividis J. Loula Jake Burga Nathan Foss Andres Campero Thomas Pouncy S. Gershman J. Tenenbaum LM&Ro 24 43 0 27 Jul 2021
Learn2Hop: Learned Optimization on Rough Landscapes Amil Merchant Luke Metz S. Schoenholz E. D. Cubuk 31 16 0 20 Jul 2021
Applications of the Free Energy Principle to Machine Learning and Neuroscience Beren Millidge DRL 22 7 0 30 Jun 2021
Action Set Based Policy Optimization for Safe Power Grid Management Bo Zhou Hongsheng Zeng Yuecheng Liu Kejiao Li Fan Wang Hao Tian 24 21 0 29 Jun 2021
Brax -- A Differentiable Physics Engine for Large Scale Rigid Body Simulation C. Freeman Erik Frey Anton Raichuk Sertan Girgin Igor Mordatch Olivier Bachem 48 351 0 24 Jun 2021
Simplifying Deep Reinforcement Learning via Self-Supervision Daochen Zha Kwei-Herng Lai Kaixiong Zhou Xia Hu SSL 49 15 0 10 Jun 2021
Analogous to Evolutionary Algorithm: Designing a Unified Sequence Model Jiangning Zhang Chao Xu Jian Li Wenzhou Chen Yabiao Wang Ying Tai Shuo Chen Chengjie Wang Feiyue Huang Yong Liu 40 22 0 31 May 2021
Multi-Agent Deep Reinforcement Learning using Attentive Graph Neural Architectures for Real-Time Strategy Games Won Joon Yun Sungwon Yi Joongheon Kim 20 10 0 21 May 2021
Differentiable Signal Processing With Black-Box Audio Effects Marco A. Martínez-Ramírez Oliver Wang Paris Smaragdis Nicholas J. Bryan 30 29 0 11 May 2021