| IMPROVING DEEP NEUROEVOLUTION VIA DEEP INNOVATION PROTECTION |
Sebastian Risi and Kenneth O. Stanley |
repo |
2020 |
| 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 |
| 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. |
[Code] |
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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
