Jeff Clune

Affiliations:
  • University of Wyoming


According to our database1, Jeff Clune authored at least 113 papers between 2005 and 2024.

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Bibliography

2024
Automated Design of Agentic Systems.
CoRR, 2024

The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery.
CoRR, 2024

OMNI-EPIC: Open-endedness via Models of human Notions of Interestingness with Environments Programmed in Code.
CoRR, 2024

Intelligent Go-Explore: Standing on the Shoulders of Giant Foundation Models.
CoRR, 2024

Scaling Instructable Agents Across Many Simulated Worlds.
CoRR, 2024


Quality Diversity through Human Feedback: Towards Open-Ended Diversity-Driven Optimization.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

OMNI: Open-endedness via Models of human Notions of Interestingness.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Quality-Diversity through AI Feedback.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Reset It and Forget It: Relearning Last-Layer Weights Improves Continual and Transfer Learning.
Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

2023
Managing AI Risks in an Era of Rapid Progress.
CoRR, 2023

Quality Diversity through Human Feedback.
CoRR, 2023

First-Explore, then Exploit: Meta-Learning Intelligent Exploration.
CoRR, 2023

Thought Cloning: Learning to Think while Acting by Imitating Human Thinking.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
Biological underpinnings for lifelong learning machines.
Nat. Mach. Intell., 2022

Evolving Multimodal Robot Behavior via Many Stepping Stones with the Combinatorial Multiobjective Evolutionary Algorithm.
Evol. Comput., 2022

Video PreTraining (VPT): Learning to Act by Watching Unlabeled Online Videos.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
First return, then explore.
Nat., 2021

Continual learning under domain transfer with sparse synaptic bursting.
CoRR, 2021

Multi-task curriculum learning in a complex, visual, hard-exploration domain: Minecraft.
CoRR, 2021

2020
Synthetic Petri Dish: A Novel Surrogate Model for Rapid Architecture Search.
CoRR, 2020

Fiber: A Platform for Efficient Development and Distributed Training for Reinforcement Learning and Population-Based Methods.
CoRR, 2020

The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities.
Artif. Life, 2020

Open Questions in Creating Safe Open-ended AI: Tensions Between Control and Creativity.
Proceedings of the 2020 Conference on Artificial Life, 2020

Generative Teaching Networks: Accelerating Neural Architecture Search by Learning to Generate Synthetic Training Data.
Proceedings of the 37th International Conference on Machine Learning, 2020

Enhanced POET: Open-ended Reinforcement Learning through Unbounded Invention of Learning Challenges and their Solutions.
Proceedings of the 37th International Conference on Machine Learning, 2020

Scaling MAP-Elites to deep neuroevolution.
Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020

Learning to Continually Learn.
Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

2019
Understanding Neural Networks via Feature Visualization: A Survey.
Proceedings of the Explainable AI: Interpreting, 2019

Designing neural networks through neuroevolution.
Nat. Mach. Intell., 2019

A deep active learning system for species identification and counting in camera trap images.
CoRR, 2019

AI-GAs: AI-generating algorithms, an alternate paradigm for producing general artificial intelligence.
CoRR, 2019

Understanding Neural Networks via Feature Visualization: A survey.
CoRR, 2019

Go-Explore: a New Approach for Hard-Exploration Problems.
CoRR, 2019

Paired Open-Ended Trailblazer (POET): Endlessly Generating Increasingly Complex and Diverse Learning Environments and Their Solutions.
CoRR, 2019

Commonsense and Semantic-Guided Navigation through Language in Embodied Environment.
Proceedings of the Visually Grounded Interaction and Language (ViGIL), 2019

An Atari Model Zoo for Analyzing, Visualizing, and Comparing Deep Reinforcement Learning Agents.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Robustness to Out-of-Distribution Inputs via Task-Aware Generative Uncertainty.
Proceedings of the International Conference on Robotics and Automation, 2019

Backpropamine: training self-modifying neural networks with differentiable neuromodulated plasticity.
Proceedings of the 7th International Conference on Learning Representations, 2019

POET: open-ended coevolution of environments and their optimized solutions.
Proceedings of the Genetic and Evolutionary Computation Conference, 2019

Evolvability ES: scalable and direct optimization of evolvability.
Proceedings of the Genetic and Evolutionary Computation Conference, 2019

2018
Automatically identifying, counting, and describing wild animals in camera-trap images with deep learning.
Proc. Natl. Acad. Sci. USA, 2018

An Atari Model Zoo for Analyzing, Visualizing, and Comparing Deep Reinforcement Learning Agents.
CoRR, 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

The Emergence of Canalization and Evolvability in an Open-Ended, Interactive Evolutionary System.
Artif. Life, 2018

Improving Exploration in Evolution Strategies for Deep Reinforcement Learning via a Population of Novelty-Seeking Agents.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

The Surprising Creativity of Digital Evolution.
Proceedings of the 2018 Conference on Artificial Life, 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 Comput. Biol., 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

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

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 Comput. Biol., 2016

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

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

Convergent Learning: Do different neural networks learn the same representations?
Proceedings of the 4th International Conference on Learning Representations, 2016

WebAL Comes of Age: A Review of the First 21 Years of Artificial Life on the Web.
Artif. 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, 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 Comput. Biol., 2015

Robots that can adapt like animals.
Nat., 2015

Understanding Neural Networks Through Deep Visualization.
CoRR, 2015

Illuminating search spaces by mapping elites.
CoRR, 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 Intell. Syst., 2014

Robots that can adapt like natural animals.
CoRR, 2014

Reports on the 2013 AAAI Fall Symposium Series.
AI Mag., 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

Summary of "The Evolutionary Origins of Modularity".
Proceedings of the Fourteenth International Conference on the Simulation and Synthesis of Living Systems, 2014

Evolved Electrophysiological Soft Robots.
Proceedings of the Fourteenth International Conference on the Simulation and Synthesis of Living Systems, 2014

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

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 Comput. Biol., 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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