Jeff Clune

According to our database1, Jeff Clune authored at least 81 papers between 2005 and 2018.

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Bibliography

2018
Evolving Multimodal Robot Behavior via Many Stepping Stones with the Combinatorial Multi-Objective Evolutionary Algorithm.
CoRR, 2018

Deep Curiosity Search: Intra-Life Exploration Improves Performance on Challenging Deep Reinforcement Learning Problems.
CoRR, 2018

VINE: An Open Source Interactive Data Visualization Tool for Neuroevolution.
CoRR, 2018

Differentiable plasticity: training plastic neural networks with backpropagation.
CoRR, 2018

The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities.
CoRR, 2018

Differentiable plasticity: training plastic neural networks with backpropagation.
Proceedings of the 35th International Conference on Machine Learning, 2018

VINE: an open source interactive data visualization tool for neuroevolution.
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2018

ES is more than just a traditional finite-difference approximator.
Proceedings of the Genetic and Evolutionary Computation Conference, 2018

Safe mutations for deep and recurrent neural networks through output gradients.
Proceedings of the Genetic and Evolutionary Computation Conference, 2018

2017
How evolution learns to generalise: Using the principles of learning theory to understand the evolution of developmental organisation.
PLoS Computational Biology, 2017

ES Is More Than Just a Traditional Finite-Difference Approximator.
CoRR, 2017

Deep Neuroevolution: Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning.
CoRR, 2017

On the Relationship Between the OpenAI Evolution Strategy and Stochastic Gradient Descent.
CoRR, 2017

Safe Mutations for Deep and Recurrent Neural Networks through Output Gradients.
CoRR, 2017

Improving Exploration in Evolution Strategies for Deep Reinforcement Learning via a Population of Novelty-Seeking Agents.
CoRR, 2017

Diffusion-based neuromodulation can eliminate catastrophic forgetting in simple neural networks.
CoRR, 2017

Automatically identifying wild animals in camera trap images with deep learning.
CoRR, 2017

The Emergence of Canalization and Evolvability in an Open-Ended, Interactive Evolutionary System.
CoRR, 2017

Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016
The Evolutionary Origins of Hierarchy.
PLoS Computational Biology, 2016

Understanding Innovation Engines: Automated Creativity and Improved Stochastic Optimization via Deep Learning.
Evolutionary Computation, 2016

Multifaceted Feature Visualization: Uncovering the Different Types of Features Learned By Each Neuron in Deep Neural Networks.
CoRR, 2016

Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space.
CoRR, 2016

Synthesizing the preferred inputs for neurons in neural networks via deep generator networks.
CoRR, 2016

WebAL Comes of Age: A Review of the First 21 Years of Artificial Life on the Web.
Artificial Life, 2016

Synthesizing the preferred inputs for neurons in neural networks via deep generator networks.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Creative Generation of 3D Objects with Deep Learning and Innovation Engines.
Proceedings of the Seventh International Conference on Computational Creativity, UPMC, Paris, France, June 27, 2016

Identifying Core Functional Networks and Functional Modules within Artificial Neural Networks via Subsets Regression.
Proceedings of the 2016 on Genetic and Evolutionary Computation Conference, Denver, CO, USA, July 20, 2016

How do Different Encodings Influence the Performance of the MAP-Elites Algorithm?
Proceedings of the 2016 on Genetic and Evolutionary Computation Conference, Denver, CO, USA, July 20, 2016

Neuromodulation Improves the Evolution of Forward Models.
Proceedings of the 2016 on Genetic and Evolutionary Computation Conference, Denver, CO, USA, July 20, 2016

Evolvability Search: Directly Selecting for Evolvability in order to Study and Produce It.
Proceedings of the 2016 on Genetic and Evolutionary Computation Conference, Denver, CO, USA, July 20, 2016

Does Aligning Phenotypic and Genotypic Modularity Improve the Evolution of Neural Networks?
Proceedings of the 2016 on Genetic and Evolutionary Computation Conference, Denver, CO, USA, July 20, 2016

2015
Neural Modularity Helps Organisms Evolve to Learn New Skills without Forgetting Old Skills.
PLoS Computational Biology, 2015

Robots that can adapt like animals.
Nature, 2015

Understanding Neural Networks Through Deep Visualization.
CoRR, 2015

Illuminating search spaces by mapping elites.
CoRR, 2015

The evolutionary origins of hierarchy.
CoRR, 2015

Convergent Learning: Do different neural networks learn the same representations?
CoRR, 2015

Convergent Learning: Do different neural networks learn the same representations?
Proceedings of the 1st Workshop on Feature Extraction: Modern Questions and Challenges, 2015

A method to improve signal quality in wireless ad-hoc networks with limited mobility.
Proceedings of the International Conference on Computing, Networking and Communications, 2015

Innovation Engines: Automated Creativity and Improved Stochastic Optimization via Deep Learning.
Proceedings of the Genetic and Evolutionary Computation Conference, 2015

Deep neural networks are easily fooled: High confidence predictions for unrecognizable images.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

2014
An Anarchy of Methods: Current Trends in How Intelligence Is Abstracted in AI.
IEEE Intelligent Systems, 2014

How transferable are features in deep neural networks?
CoRR, 2014

Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images.
CoRR, 2014

Robots that can adapt like natural animals.
CoRR, 2014

Reports on the 2013 AAAI Fall Symposium Series.
AI Magazine, 2014

How transferable are features in deep neural networks?
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Novelty search creates robots with general skills for exploration.
Proceedings of the Genetic and Evolutionary Computation Conference, 2014

Encouraging creative thinking in robots improves their ability to solve challenging problems.
Proceedings of the Genetic and Evolutionary Computation Conference, 2014

Evolving neural networks that are both modular and regular: HyperNEAT plus the connection cost technique.
Proceedings of the Genetic and Evolutionary Computation Conference, 2014

Automated generation of environments to test the general learning capabilities of AI agents.
Proceedings of the Genetic and Evolutionary Computation Conference, 2014

2013
Hands-free Evolution of 3D-printable Objects via Eye Tracking
CoRR, 2013

Natural selection fails to optimize mutation rates for long-term adaptation on rugged fitness landscapes.
Proceedings of the Genetic and Evolutionary Computation Conference, 2013

Summary of "the evolutionary origins of modularity".
Proceedings of the Genetic and Evolutionary Computation Conference, 2013

Unshackling evolution: evolving soft robots with multiple materials and a powerful generative encoding.
Proceedings of the Genetic and Evolutionary Computation Conference, 2013

Evolving Gaits for Physical Robots with the HyperNEAT Generative Encoding: The Benefits of Simulation.
Proceedings of the Applications of Evolutionary Computation - 16th European Conference, 2013

Upload any object and evolve it: Injecting complex geometric patterns into CPPNS for further evolution.
Proceedings of the IEEE Congress on Evolutionary Computation, 2013

Preface.
Proceedings of the 2013 AAAI Fall Symposia, Arlington, Virginia, USA, November 15-17, 2013, 2013

Organizing Committee.
Proceedings of the 2013 AAAI Fall Symposia, Arlington, Virginia, USA, November 15-17, 2013, 2013

2012
The evolutionary origins of modularity
CoRR, 2012

Aracna: An Open-Source Quadruped Platform for Evolutionary Robotics.
Proceedings of the Artificial Life 13: Proceedings of the Thirteenth International Conference on the Simulation and Synthesis of Living Systems, 2012

2011
On the Performance of Indirect Encoding Across the Continuum of Regularity.
IEEE Trans. Evolutionary Computation, 2011

Generating gaits for physical quadruped robots: evolved neural networks vs. local parameterized search.
Proceedings of the 13th Annual Genetic and Evolutionary Computation Conference, 2011

A novel generative encoding for evolving modular, regular and scalable networks.
Proceedings of the 13th Annual Genetic and Evolutionary Computation Conference, 2011

Evolving robot gaits in hardware: the HyperNEAT generative encoding vs. parameter optimization.
Proceedings of the Advances in Artificial Life: 20th Anniversary Edition, 2011

Natural selection fails to optimize mutation rates for long-term adaptation on rugged fitness landscapes.
Proceedings of the Advances in Artificial Life: 20th Anniversary Edition, 2011

Evolving three-dimensional objects with a generative encoding inspired by developmental biology.
Proceedings of the Advances in Artificial Life: 20th Anniversary Edition, 2011

Selective pressures for accurate altruism targeting: evidence from digital evolution for difficult-to-test aspects of inclusive fitness theory.
Proceedings of the Advances in Artificial Life: 20th Anniversary Edition, 2011

2010
Investigating whether hyperNEAT produces modular neural networks.
Proceedings of the Genetic and Evolutionary Computation Conference, 2010

Digital evolution with avida.
Proceedings of the Genetic and Evolutionary Computation Conference, 2010

2009
Problem decomposition using indirect reciprocity in evolved populations.
Proceedings of the Genetic and Evolutionary Computation Conference, 2009

The sensitivity of HyperNEAT to different geometric representations of a problem.
Proceedings of the Genetic and Evolutionary Computation Conference, 2009

The Evolution of Division of Labor.
Proceedings of the Advances in Artificial Life. Darwin Meets von Neumann, 2009

HybrID: A Hybridization of Indirect and Direct Encodings for Evolutionary Computation.
Proceedings of the Advances in Artificial Life. Darwin Meets von Neumann, 2009

Evolving coordinated quadruped gaits with the HyperNEAT generative encoding.
Proceedings of the IEEE Congress on Evolutionary Computation, 2009

2008
Natural Selection Fails to Optimize Mutation Rates for Long-Term Adaptation on Rugged Fitness Landscapes.
PLoS Computational Biology, 2008

How a Generative Encoding Fares as Problem-Regularity Decreases.
Proceedings of the Parallel Problem Solving from Nature, 2008

How generative encodings fare on less regular problems.
Proceedings of the Genetic and Evolutionary Computation Conference, 2008

2007
Investigating the Emergence of Phenotypic Plasticity in Evolving Digital Organisms.
Proceedings of the Advances in Artificial Life, 9th European Conference, 2007

2005
Investigations in meta-GAs: panaceas or pipe dreams?
Proceedings of the Genetic and Evolutionary Computation Conference, 2005


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