ES Is More Than Just a Traditional Finite-Difference Approximator

18 December 2017

Jeff Clune

Papers citing "ES Is More Than Just a Traditional Finite-Difference Approximator"

24 / 24 papers shown

Title
Questioning Representational Optimism in Deep Learning: The Fractured Entangled Representation Hypothesis Akarsh Kumar Jeff Clune Joel Lehman Kenneth O. Stanley OOD 21 0 0 16 May 2025
ETGL-DDPG: A Deep Deterministic Policy Gradient Algorithm for Sparse Reward Continuous Control Ehsan Futuhi Shayan Karimi Chao Gao Martin Müller 43 1 0 07 Oct 2024
Evolutionary Strategy Guided Reinforcement Learning via MultiBuffer Communication Adam Callaghan Karl Mason Patrick Mannion 37 2 0 20 Jun 2023
EvoTorch: Scalable Evolutionary Computation in Python N. E. Toklu Timothy James Atkinson Vojtvech Micka Paweł Liskowski R. Srivastava 22 12 0 24 Feb 2023
Training Diverse High-Dimensional Controllers by Scaling Covariance Matrix Adaptation MAP-Annealing Bryon Tjanaka Matthew C. Fontaine David H. Lee Aniruddha Kalkar Stefanos Nikolaidis 68 8 0 06 Oct 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
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
Approximating Gradients for Differentiable Quality Diversity in Reinforcement Learning Bryon Tjanaka Matthew C. Fontaine Julian Togelius Stefanos Nikolaidis 38 50 0 08 Feb 2022
Automated Reinforcement Learning (AutoRL): A Survey and Open Problems Jack Parker-Holder Raghunandan Rajan Xingyou Song André Biedenkapp Yingjie Miao ... Vu-Linh Nguyen Roberto Calandra Aleksandra Faust Frank Hutter Marius Lindauer AI4CE 33 100 0 11 Jan 2022
Can Transfer Neuroevolution Tractably Solve Your Differential Equations? Jian Cheng Wong Abhishek Gupta Yew-Soon Ong 28 21 0 06 Jan 2021
Effective Diversity in Population Based Reinforcement Learning Jack Parker-Holder Aldo Pacchiano K. Choromanski Stephen J. Roberts 22 158 0 03 Feb 2020
Provably Robust Blackbox Optimization for Reinforcement Learning K. Choromanski Aldo Pacchiano Jack Parker-Holder Yunhao Tang Deepali Jain Yuxiang Yang Atil Iscen Jasmine Hsu Vikas Sindhwani 13 5 0 07 Mar 2019
Evolutionary Stochastic Gradient Descent for Optimization of Deep Neural Networks Xiaodong Cui Wei Zhang Zoltán Tüske M. Picheny ODL 16 89 0 16 Oct 2018
CEM-RL: Combining evolutionary and gradient-based methods for policy search Aloïs Pourchot Olivier Sigaud 32 160 0 02 Oct 2018
Switching Isotropic and Directional Exploration with Parameter Space Noise in Deep Reinforcement Learning Izumi Karino Kazutoshi Tanaka Ryuma Niiyama Y. Kuniyoshi 19 3 0 18 Sep 2018
Towards Distributed Coevolutionary GANs Abdullah Al-Dujaili Tom Schmiedlechner Erik Hemberg Una-May O’Reilly GAN 36 41 0 21 Jul 2018
Encoding Motion Primitives for Autonomous Vehicles using Virtual Velocity Constraints and Neural Network Scheduling M. Plessen 17 1 0 05 Jul 2018
Multi-objective Model-based Policy Search for Data-efficient Learning with Sparse Rewards Rituraj Kaushik Konstantinos Chatzilygeroudis Jean-Baptiste Mouret 31 19 0 25 Jun 2018
Challenges in High-dimensional Reinforcement Learning with Evolution Strategies Nils Müller Tobias Glasmachers 33 28 0 04 Jun 2018
Structured Evolution with Compact Architectures for Scalable Policy Optimization K. Choromanski Mark Rowland Vikas Sindhwani Richard Turner Adrian Weller 22 147 0 06 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
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
On the Relationship Between the OpenAI Evolution Strategy and Stochastic Gradient Descent Xingwen Zhang Jeff Clune Kenneth O. Stanley 25 57 0 18 Dec 2017