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Alro10
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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

Table of Contents

Papers

| Title | Authors | Code | Year | | ----- | ------- | -------- | ---- | | Learning and Implementing Deep Learning Methods | Omar Awwad | not yet | 2020 | | Generating CNNs using Genetic Algorithm | Lev Martin Zachar | not yet | 2020 | | A Neuroevolutionary Approach to Evolve a Flexible Neural Controller for a Morphology Changing Quadruped Robot | -Wonho Lee | not yet | 2020 | | Evolutionary Reinforcement Learning via Cooperative Coevolutionary Negatively Correlated Search | Hu Zhang, et al. | not yet | 2020 | | CLAN: Continuous Learning using Asynchronous Neuroevolution on Commodity Edge Devices | Parth Mannan, et al. | not yet | 2020 | | Using Deep Neuroevolution to train Deep Reinforcement Learning Agents | Muhammad Salik Nadeem | not yet | 2020 | | Analyzing the Components of Distributed Coevolutionary GAN Training | Jamal Toutouh, et al. | [repo] | 2020 | | 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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