Alro10/ awesome-deep-neuroevolution
Need help with awesome-deep-neuroevolution?
Click the “chat” button below for chat support from the developer who created it, or find similar developers for support.
About the developer
179 Stars 
34 Forks 
Apache License 2.0 
287 Commits 
1 Opened issues 
Description
A collection of Deep Neuroevolution resources or evolutionary algorithms applying in Deep Learning (constantly updating)
Services available
Contributors list
Readme
Awesome Deep Neuroevolution
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]
| 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 | repo | 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 | 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] | 2018, AAMAS 2019 |
| Simple random search provides a competitive approach to reinforcement learning| Horia Mania, Aurelia Guy, Benjamin Recht | [repo] | 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 | 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] [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] [blog]| 2017 |
| Safe Mutations for Deep and Recurrent Neural Networks through Output Gradients | Joel Lehman, Jay Chen, Jeff Clune, Kenneth O. Stanley | repo | 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 | repo | 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 |
Conferences
- Genetic and evolutionary computation
- Machine learning
- Artificial intelligence
- Games
Tutorials
- Paper experiments replication: Deep Neuroevolution Uber
- Genetic Algorithm for 2D function-Matlabgithub
Resources
- VINE: An Open Source Interactive Data Visualization Tool for Neuroevolution by Uber AI Labs.
- EvoGrad: A Lightweight Library for Gradient-Based Evolution by Uber AI Labs.
- POET by Uber AI Labs.
- Nevergrad - A gradient-free optimization platform by Facebook Research.
Researchers
- Kenneth O. Stanley- Uber AI Labs.
- Jeff Clune- Open AI.
- Risto Miikkulainen- University of Texas at Austin.
- Nuno Lourenço- University of Coimbra.
Know of a recent paper? Send a pull request or open an issue! :+1: