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A collection of Deep Neuroevolution resources or evolutionary algorithms applying in Deep Learning (constantly updating)

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Awesome Deep Neuroevolution

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A collection of Deep Neuroevolution and evolutionary computation resources. Inspired by awesome-deep-learning-papers, awesome-meta-learning, the early paper by OpenAI-Evolution Strategies and the amazing work from Uber AI Labs blog

A good survey of Deep Reinforcement Learning: A Brief Survey of Deep Reinforcement Learning

Papers

Title Authors Code Year
Developmental neuronal networks as models to study the evolution of biological intelligence Arend Hintze, et al. not yet 2020
CoNES: Convex Natural Evolutionary Strategies Sushant Veer and Anirudha Majumdar [repo] 2020
One-Shot Neural Architecture Search via Novelty Driven Sampling Miao Zhang, et al. [repo] IJCAI-20
Coevolutionary Learning of Neuromodulated Controllers for Multi-Stage and Gamified Tasks Chloe M. Barnes, et al. not yet 2020
An adaptive neuroevolution-based hyperheuristic Etor Arza, et al. repo GECCO ’20
Learning to walk - reward relevance within an enhanced neuroevolution approach I. Colucci, et al. not yet GECCO ’20
Evolving neural network agents to play atari games with compact state representations Adam Tupper, et al. not yet GECCO ’20
Online NEAT for Credit Evaluation - a Dynamic Problem with Sequential Data Yue Liu, et al. not yet 2020
Exploring the evolution of GANs through quality diversity Victor Costa, et al. [repo] GECCO ’20
Improving neuroevolutionary transfer learning of deep recurrent neural networks through network-aware adaptation AbdElRahman ElSaid, et al. [repo] GECCO ’20
Online Hyper-parameter Tuning in Off-policy Learning via Evolutionary Strategies Yunhao Tang and Krzysztof Choromanski not yet 2020
NEUROEVOLUTIONARY TRANSFER LEARNING OF DEEP RECURRENT NEURAL NETWORKS THROUGH NETWORK-AWARE ADAPTATION AbdElRahman ElSaid, et al. not yet 2020
Combining a gradient-based method and an evolution strategy for multi-objective reinforcement learning Diqi Chen, et al. not yet 2020
Efficient Architecture Search for Deep Neural Networks Ram Deepak Gottapu and Cihan H Dagli not yet 2020
Evolutionary Automation of Coordinated Autonomous Vehicles Allen Huang and Geoff Nitschke not yet 2020
Synthetic Petri Dish: A Novel Surrogate Model for Rapid Architecture Search Aditya Rawal not yet 2020
TRAINING ADAPTABLE NEURAL NETWORKS BASED ON EVOLVABILITY SEARCH Gajewski, Alexander P, et al. not 2020
IMPROVING NEUROEVOLUTION USING ISLAND EXTINCTION AND REPOPULATION Zimeng Lyu, et al. [repo] 2020
Evolutionary Population Curriculum for Scaling Multi-Agent Reinforcement Learning Qian LONG not Master Thesis 2020
Novelty Search makes Evolvability Inevitable Stephane Doncieux, et al. [repo] GECCO 2020
Genetic Deep Reinforcement Learning for Mapless Navigation Enrico Marchesini and Alessandro Farinelli not yet AAMAS 2020
Accelerating Deep Neuroevolution on Distributed FPGAs for Reinforcement Learning Problems Alexis Asseman, et al. [repo] 2020 IBM Almaden Research Center
A Hybrid Method for Training Convolutional Neural Networks Vasco Lopes and Paulo Fazendeiro noy yet 2020
An Effective Maximum Entropy Exploration Approach for Deceptive Game in Reinforcement Learning Chunmao Lin, et al. not yet Neurocomputing 2020
A Comparison of Evolutionary and Tree-Based Approaches for Game Feature Validation in RealTime Strategy Games with a Novel Metric Damijan Novak, et al. not yet 2020
First return then explore Adrien Ecoffet*, Joost Huizinga∗, Joel Lehman, Kenneth O. Stanley & Jeff Clune [repo] 2020
Neuromodulated multiobjective evolutionary neurocontrollers without speciation Ian Showalter and Howard M. Schwartz not yet Evolutionary Intelligence (2020)
PBCS: Efficient Exploration and Exploitation Using a Synergy between Reinforcement Learning and Motion Planning Guillaume Matheron, et al. not yet 2020
Efficient Evolutionary Neural Architecture Search (NAS) by Modular Inheritable Crossover Hao Tan, et al. not yet BIC-TA 2020
Diversity Preservation in Minimal Criterion Coevolution through Resource Limitation Jonathan C. Brant and Kenneth O. Stanley not yet GECCO 2020
Meta-Learning in Neural Networks: A Survey Timothy Hospedales, et al. not, survey 2020
Improving Deep Reinforcement Learning with Advanced Exploration and Transfer Learning Techniques HAIYAN YIN not, PhD Thesis 2020
Using Skill Rating as Fitness on the Evolution of GANs Vitor Costa not yet EvoApplications 2020
ModuleNet: Knowledge-inherited Neural Architecture Search Yaran Chen, et al. repo 2020
The Expense of Neuro-Morpho Functional Machines Scott Hallauer and Geoff Nitschke repo 2020
Adversarial genetic programming for cyber security: a rising application domain where GP matters Una-May O’Reilly, et al. not yet Genetic Programming and Evolvable Machines 2020
Evolutionary recurrent neural network for image captioning Hanzhang Wang, et al. not yet Neurocomputing 2020 Elsevier
Learning Stabilizing Control Policies for a Tensegrity Hopper with Augmented Random Search Vladislav Kurenkov, et al. not yet 2020
Evolution of Scikit-Learn Pipelines with Dynamic Structured Grammatical Evolution Filipe Assunção, et al. not yet 2020
Incremental Evolution and Development of Deep Artificial Neural Networks Filipe Assunção, et al. repo 2020
Interactive Evolution and Exploration Within Latent Level-Design Space of Generative Adversarial Networks Jacob Schrum, et al. repo GECCO 2020
EvoU–Net: An Evolutionary Deep Fully Convolutional NeuralNetwork for Medical Image Segmentation Tahereh Hassanzadeh, et al. not yet 2020 ACM
Understanding Features on Evolutionar y Policy Optimizations Sangyeop Lee, et al. not yet 2020 ACM
Fiber: A Platform for Efficient Development and Distributed Training for Reinforcement Learning and Population-Based Methods Jiale Zhi, et al. not yet 2020
EVOLUTIONARY POPULATION CURRICULUM FOR SCALING MULTI-AGENT REINFORCEMENT LEARNING Qian Long, et al. repo ICLR 2020
Optimisation of Phonetic Aware Speech Recognition through Multi-objective Evolutionary Algorithms Jordan J. Bird, et al. not yet Elsevier
A Brain-Inspired Framework for Evolutionary Artificial General Intelligence Mohammad Nadji-Tehrani, et al. not yet 2020
The use of Genetic Programming for detecting the incorrect predictions of Classification Models Adrianna Maria Napiórkowska not, Master thesis 2020
Hyper-Parameter Selection in Convolutional Neural Networks Using Microcanonical Optimization Algorithm AYLA GÜLCÜ and ZEKI KUŞ not yet 2020
Enhanced POET: Open-Ended Reinforcement Learning through Unbounded Invention of Learning Challenges and their Solutions Rui Wang, et al. not yet 2020
Neuroevolution of Self-Interpretable Agents Yujin Tang, et al. repo 2020
META-LEARNING CURIOSITY ALGORITHMS Ferran Alet, et al. repo ICLR 2020
Learning feature spaces for regression with genetic programming William La Cava and Jason H. Moore not yet Genetic Programming and Evolvable Machines (2020)
Artificial Neural Network Trained by Plant Genetic-Inspired Optimizer Neeraj Gupta, et al. not yet Frontier Applications of Nature Inspired Computation 2020
Action Unit Analysis Enhanced Facial Expression Recognition by Deep Neural Network Evolution Ruicong Zhi, et al. not yet Neurocomputing 2020 Elsevier
Coping with opponents: multi-objective evolutionary neural networks for fighting games Steven Kunzel and Silja Meyer-Nieberg not yet Neural Computing and Applications (2020)
Evolved Neuromorphic Control for High Speed Divergence-based Landings of MAVs Jesse J. Hagenaars, et al. repo 2020
EGAD! an Evolved Grasping Analysis Dataset for diversity and reproducibility in robotic manipulation Douglas Morrison, et al. code-blog 2020
Scaling MAP-Elites to Deep Neuroevolution Cedric Colac, et al. not yet 2020
Backpropamine: training self-modifying neural networks with differentiable neuromodulated plasticity Aditya Rawal, Jeff Clune, Kenneth O. Stanley not yet 2020
AN EVOLUTIONARY DEEP LEARNING METHOD FOR SHORT-TERM WIND SPEED PREDICTION: A CASE STUDY OF THE LILLGRUND OFFSHORE WIND FARM Mehdi Neshat, et al. not yet 2020
Accelerating Reinforcement Learning with a Directional-Gaussian-Smoothing Evolution Strategy Jiaxin Zhang, et al. not yet 2020
Comparison Between Stochastic Gradient Descent and VLE Metaheuristic for Optimizing Matrix Factorization Juan A. Gómez-Pulido, et al. not yet OLA 2020
Effective Reinforcement Learning through Evolutionary Surrogate-Assisted Prescription Olivier Francon, et al. not yet 2020
Highly Efficient Deep Intelligence via Multi-Parent Evolutionary Synthesis of Deep Neural Networks Audrey Chung Master Thesis 2020
NEUROEVOLUTION OF NEURAL NETWORK ARCHITECTURES USING CODEEPNEAT AND KERAS Jonas da Silveira Bohrer, et al. repo 2020
Horizontal gene transfer for recombining graphs Timothy Atkinson, et al. repo Genetic Programming and Evolvable Machines (2020)
Evolutionary music: applying evolutionary computation to the art of creating music Roisin Loughran, et al. not yet Genetic Programming and Evolvable Machines (2020)
Improving the Performance of Evolutionary Algorithms via Gradient-Based Initialization Chris Waites, et al not yet 2020
Evolving Loss Functions With Multivariate Taylor Polynomial Parameterizations Santiago Gonzalez and Risto Miikkulainen repo 2020
Evolving Neural Networks through a Reverse Encoding Tree Haoling Zhang, et al. repo 2020
Evolutionary LSTM-FCN networks for pattern classification in industrial processes Patxi Ortego, et al. not yet Swarm and Evolutionary Computation, May 2020
Evolving deep neural networks using coevolutionary algorithms with multi-population strategy Sreenivas Sremath Tirumala not yet Neural Computing and Applications 2020
Hierarchy and co-evolution processes in urban systems Juste Raimbault repo 2020
A Study of Fitness Landscapes for Neuroevolution Nuno M. Rodrigues, et al. not yet 2020
Combining Evolution and Learning in Computational Ecosystems Claes Strannegård, et al. not yet 2020
Examining Hyperparameters of Neural Networks Trained Using Local Search Ahmed Aly, et al. not yet 2020
Analysing Deep Reinforcement Learning Agents Trained with Domain Randomisation Tianhong Dai, et al. not yet 2020
POPULATION-GUIDED PARALLEL POLICY SEARCH FOR REINFORCEMENT LEARNING Whiyoung Jung, et al. repo ICLR 2020
IMPROVING DEEP NEUROEVOLUTION VIA DEEP INNOVATION PROTECTION Sebastian Risi and Kenneth O. Stanley repo 2020
Evolutionary NetArchitecture Search for Deep Neural Networks Pruning Shuxin Chen, et al. not yet 2019
AI-GAs: AI-generating algorithms, an alternate paradigm for producing general artificial intelligence Jeff Clune not yet 2019
Differential Evolution for Neural Networks Optimization Marco Baioletti, et al. not yet Mathematics 2020
Neuro-Evolution Search Methodologies for Collective Self-Driving Vehicles Chien-Lun (Allen) Huang Master thesis 2019
Using Neuroevolved Binary Neural Networks to solve reinforcement learning environments Raul Valencia, et al. not yet 2019 IEEE APCCAS
Neuroevolution with CMA-ES for Real-time Gain Tuning of a Car-like Robot Controller Ashley Hill, et al not yet ICINCO 2019
Learning to grow: control of materials self-assembly using evolutionary reinforcement learning Stephen Whitelam, et al. not yet 2019
Network of Evolvable Neural Units: Evolving to Learn at a Synaptic Level Paul Bertens, et al. not yet 2019
GENERATIVE TEACHING NETWORKS: ACCELERATING NEURAL ARCHITECTURE SEARCH BY LEARNING TO GENERATE SYNTHETIC TRAINING DATA Felipe Petroski Such, et al. not yet 2019
Efficacy of Modern Neuro-Evolutionary Strategies for Continuous Control Optimization Paolo Pagliuca, et al. not yet 2019
GAIM: A C++ library for Genetic Algorithms and Island Models Georgios Detorakis, et al. [repo] JOSS 2019
Dynamic Facial Feature Learning by Deep Evolutionary Neural Networks Ruicong Zhi, et al. not yet CyberDI 2019
Automatic Design of Convolutional Neural Networks using Grammatical Evolution Ricardo Henrique Remes de Lima, et al. not yet BRACIS 2019
Q-NAS Revisited: Exploring Evolution Fitness to Improve Efficiency Daniela Szwarcman, et al noy yet BRACIS 2019
An Evolutionary Approach to Compact DAG Neural Network Optimization Carter Chiu, et al. not yet 2019
Multi-Criterion Evolutionary Design of Deep Convolutional Neural Networks Zhichao Lu, et al. [repo] 2019
A Survey on the Latest Development of Machine Learning in Genetic Algorithm and Particle Swarm Optimization Dipti Kapoor Sarmah not yet Optimization in Machine Learning and Applications
A Graph-Based Encoding for Evolutionary Convolutional Neural Network Architecture Design William Irwin-Harris, et al. not yet 2019 IEEE Congress on Evolutionary Computation (CEC)
Auto-creation of Effective Neural Network Architecture by Evolutionary Algorithm and ResNet for Image Classification Zefeng Chen, et al. not yet 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC)
Evolving Knowledge And Structure Through Evolution-based Neural Architecture Search Magnus Poppe Wang not Master Thesis 2019
Procedural Generation of Quests for Games Using Genetic Algorithms and Automated Planning Edirlei Soares de Lima, et al. not yet SBGames 2019
Culturally Evolved GANs for generating Fake Stroke Faces Kaitav Mehta, et al. code not yet 2019
Neuroevolutionary Training of Deep Convolutional Generative Adversarial Networks Kaitav Mehta not Master Thesis 2019
UMA ESTRUTURA PARA EXECUCAO DE REDES NEURAIS EVOLUTIVAS NA GPU Jorge Rama Krsna Mandoju not Master Thesis 2019
An Overview of Open-Ended Evolution: Editorial Introduction to the Open-Ended Evolution II Special Issue Norman Packard, et al. not yet 2019
Deep neural network architecture search using network morphism Arkadiusz Kwasigroch, et al. [repo]github 2019
Neuroevolutive Algorithms for Learning Gaits in Legged Robots Pablo Reyes, et al. not yet 2019
Neural Architecture Evolution in Deep Reinforcement Learning for Continuous Control Jörg K.H. Franke and Gregor Koehler, et al. not yet 2019
Efficient Decoupled Neural Architecture Search by Structure and Operation Sampling Heung-Chang Lee, et al. repo 2019
ES-MAML: Simple Hessian-Free Meta Learning Xingyou Song, et al. not yet 2019
Empirical study on the performance of Neuro Evolution of Augmenting Topologies (NEAT) Domen Vake, et al. repo 2019
Improving Gradient Estimation in Evolutionary Strategies With Past Descent Directions Florian Meier and Asier Mujika not yet 2019
Algebraic Neural Architecture Representation, Evolutionary Neural Architecture Search, and Novelty Search in Deep Reinforcement Learning Ethan C. Jackson not PhD Thesis 2019
GACNN: TRAINING DEEP CONVOLUTIONAL NEURAL NETWORKS WITH GENETIC ALGORITHM Parsa Esfahanian and Mohammad Akhavan not yet 2019
Implicit Multi-Objective Coevolutionary Algorithms Adefunke Akinola not Master Thesis 2019
CEM-RL: Combining evolutionary and gradient-based methods for policy search Aloïs Pourchot, Olivier Sigaud repogithub ICLR 2019
Efficient Multi-objective Neural Architecture Search via Lamarckian Evolution Thomas Elsken, Jan Hendrik Metzen, Frank Hutter openreview 2018, ICLR2019
Exploring Randomly Wired Neural Networks for Image Recognition Saining Xie, Alexander Kirillov, Ross Girshick, Kaiming He not yet 2019
Designing neural networks through neuroevolution Kenneth O. Stanley, Jeff Clune, Joel Lehman and Risto Miikkulainen it is a letter Nature machine intelligence January 2019
Guided evolutionary strategies: escaping the curse of dimensionality in random search Niru Maheswaranathan, Luke Metz, George Tucker, Dami Choi, Jascha Sohl-Dickstein repo github ICML 2019
Collaborative Evolutionary Reinforcement Learning Shauharda Khadka, Somdeb Majumdar, Tarek Nassar, Zach Dwiel, Evren Tumer, Santiago Miret, Yinyin Liu, Kagan Tumer blog ICML 2019
Trust Region Evolution Strategies Guoqing Liu et al. not yet AAAI 2019
Deep Neuroevolution of Recurrent and Discrete World Models Sebastian Risi, Kenneth O. Stanley repo 2019
Proximal Distilled Evolutionary Reinforcement Learning Cristian Bodnar, Ben Day, Pietro Lio' not yet AAAI 2019
POET: open-ended coevolution of environments and their optimized solutions Rui Wang, Joel Lehman, Jeff Clune and Kenneth O. Stanley not yet GECCO 2019
COEGAN: evaluating the coevolution effect in generative adversarial networks V. Costa, N. Lourenço, J. Correia, and P. Machado repo GECCO 2019
Evolution and self-teaching in neural networks: another comparison when the agent is more primitively conscious Nam Le not yet GECCO 2019
Diverse Agents for Ad-Hoc Cooperation in Hanabi Rodrigo Canaan, Julian Togelius, Andy Nealen, Stefan Menzel not yet CoG 2019
EPNAS: Efficient Progressive Neural Architecture Search Yanqi Zhou, Peng Wang, Sercan Arik, Haonan Yu, Syed Zawad, Feng Yan, Greg Diamos not yet 2019
Acoustic Model Optimization Based On Evolutionary Stochastic Gradient Descent with Anchors for Automatic Speech Recognition Xiaodong Cui, Michael Picheny (IBM Research) not yet Interspeech 2019
Fast DENSER: Efficient Deep NeuroEvolution Filipe Assunção, Nuno Lourenço, Penousal Machado, Bernardete Ribeiro repo EuroGP 2019
AlphaStar: An Evolutionary Computation Perspective Kai Arulkumaran, Antoine Cully, Julian Togelius not yet GECCO 2019
Automatic Design of Artificial Neural Networks for Gamma-Ray Detection Filipe Assunção, João Correia, Rúben Conceição, Mário Pimenta, Bernardo Tomé, Nuno Lourenço, Penousal Machado not yet 2019
Evolvability ES: Scalable and Direct Optimization of Evolvability Alexander Gajewski, Jeff Clune, Kenneth O. Stanley, Joel Lehman repo GECCO 2019
Towards continual reinforcement learning through evolutionary meta-learning Djordje Grbic and Sebastian Risi not yet GECCO 2019
Automated Neural Network Construction with Similarity Sensitive Evolutionary Algorithms Haiman Tian et al. not yet 2019
Provably Robust Blackbox Optimization for Reinforcement Learning Krzysztof Choromanski, Aldo Pacchiano et al. not yet 2019
Go-Explore: a New Approach for Hard-Exploration Problems Adrien Ecoffet, Joost Huizinga, Joel Lehman, Kenneth O. Stanley, Jeff Clune not yet 2019
Culturally Evolved GANs for Generating Fake Stroke Faces Kaitav Mehta et al. not yet ICTS4eHealth'19
An Evolution Strategy with Progressive Episode Lengths for Playing Games Lior Fuks, Noor Awad , Frank Hutter and Marius Lindauer repo IJCAI 2019
On Hard Exploration for Reinforcement Learning: A Case Study in Pommerman Chao Gao, Bilal Kartal, Pablo Hernandez-Leal, Matthew E. Taylor not yet 2019
A Knee-Guided Evolutionary Algorithm for Compressing Deep Neural Networks Yao Zhou, et al. not yet 2019
Multi-task Deep Reinforcement Learning with Evolutionary Algorithm and Policy Gradients Method in 3D Control Tasks Shota Imai et al. not yet In book: Big Data, Cloud Computing, and Data Science Engineering 2019
Evolutionary deep learning E Dufourq not PhD thesis 2019
Guiding Evolutionary Strategies with Off-Policy Actor-Critic Yunhao Tang not yet 2019
Construction of Macro Actions for Deep Reinforcement Learning Yi-Hsiang Chang, Kuan-Yu Chang, Henry Kuo, Chun-Yi Lee not yet 2019
Fast Automatic Optimisation of CNN Architectures for Image Classification Using Genetic Algorithm Ali Bakhshi, et al. not yet CEC 2019
Memetic Evolution Strategy for Reinforcement Learning Xinghua Qu, et al. not yet 2019
Epigenetic evolution of deep convolutional models Alexander Hadjiivanov and Alan Blair not yet CEC 2019
A CROSS-DATA SET EVALUATION OF GENETICALLY EVOLVED NEURAL NETWORK ARCHITECTURES Ben Gelman not yet Master Thesis 2019
Architecture Search by Estimation of Network Structure Distributions Anton Muravev, et al. not yet 2019
Evolving unsupervised neural networks for Slither.io Mitchell Miller, et al. Slither.io FDG 2019
Scalable Reinforcement-Learning-Based Neural Architecture Search for Cancer Deep Learning Research Prasanna Balaprakash and Romain Egele, et al. not yet 2019
Using Neuroevolution for Predicting Mobile Marketing Conversion Pedro José Pereira, et al. not yet LNCS, volume 11805
A Restart-based Rank-1 Evolution Strategy for Reinforcement Learning Zefeng Chen, et al. not yet IJCAI-19
Evolution of Kiting Behavior in a Two Player Combat Problem Pavlos Androulakakis and Zachariah E. Fuchs not yet IEEE COG 2019
Learning to Select Mates in Evolving Non-playable Characters Dylan R. Ashley, et al. not yet IEEE COG 2019
MULTI-SPECIES EVOLUTIONARY ALGORITHMS FOR COMPLEX OPTIMISATION PROBLEMS XIAOFEN LU not yet PhD thesis at University of Birmingham
ATTRACTION-REPULSION ACTOR-CRITIC FOR CONTINUOUS CONTROL REINFORCEMENT LEARNING Thang Doan and Bogdan Mazoure, et al. not yet 2019
Comparative Study of Neuro-Evolution Algorithms in Reinforcement Learning for Self-Driving Cars Ahmed AbuZekry, et al. not yet 2019
An Empirical Exploration of Deep Recurrent Connections and Memory Cells Using Neuro-Evolution Travis J. Desell, et al. repo 2019
THE ANT SWARM NEURO-EVOLUTION PROCEDURE FOR OPTIMIZING RECURRENT NETWORKS AbdElRahman A. ElSaid, et al. not yet 2019
Correlation Analysis-Based Neural Network Self-Organizing Genetic Evolutionary Algorithm ZENGHAO CHAI, et al. not yet IEEE Access 2019
Learning Task-specific Activation Functions using Genetic Programming Mina Basirat and Peter M. Roth repo 2019
A HYBRID NEURAL NETWORK AND GENETIC PROGRAMMING APPROACH TO THE AUTOMATIC CONSTRUCTION OF COMPUTER VISION SYSTEMS Cameron P. Kyle-Davidson not Master Thesis 2019
Novelty Search for Deep Reinforcement Learning Policy Network Weights by Action Sequence Edit Metric Distance Ethan C. Jackson and Mark Daley repo Submitted to GECCO 2019
Playing Atari with Six Neurons Giuseppe Cuccu, Julian Togelius, Philippe Cudre-Mauroux [repo] github 2018, AAMAS 2019
Simple random search provides a competitive approach to reinforcement learning Horia Mania, Aurelia Guy, Benjamin Recht [repo]github 2018
Regularized Evolution for Image Classifier Architecture Search Esteban Real, Alok Aggarwal, Yanping Huang, Quoc V Le repocolab 2018, AAAI 2019
Evolution-Guided Policy Gradient in Reinforcement Learning Shauharda Khadka, Kagan Tumer repo github NIPS 2018
Evolutionary Stochastic Gradient Descent for Optimization of Deep Neural Networks Xiaodong Cui, Wei Zhang, Zoltán Tüske, Michael Picheny not yet NIPS 2018
Experimental Evaluation of Metaheuristic Optimization of Gradients as an Alternative to Backpropagation Oleksandr Zavalnyi et al. not yet 2018
Evolution Strategies as a Scalable Alternative to Reinforcement Learning Tim Salimans, Jonathan Ho, Xi Chen, Szymon Sidor, Ilya Sutskever [repo]github [blog] 2017
Deep Neuroevolution: Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning Felipe Petroski Such, Vashisht Madhavan, Edoardo Conti, Joel Lehman, Kenneth O. Stanley, Jeff Clune [repo]github [blog] 2017
Safe Mutations for Deep and Recurrent Neural Networks through Output Gradients Joel Lehman, Jay Chen, Jeff Clune, Kenneth O. Stanley repogithub 2017
Improving Exploration in Evolution Strategies for Deep Reinforcement Learning via a Population of Novelty-Seeking Agents Edoardo Conti, Vashisht Madhavan, Felipe Petroski Such, Joel Lehman, Kenneth O. Stanley, Jeff Clune repogithub 2017, NIPS 2018
On the Relationship Between the OpenAI Evolution Strategy and Stochastic Gradient Descent Xingwen Zhang, Jeff Clune, Kenneth O. Stanley blog 2017
ES Is More Than Just a Traditional Finite-Difference Approximator Joel Lehman, Jay Chen, Jeff Clune, Kenneth O. Stanley blog 2017

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