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06/17/2022
Evolution through Large Models
This paper pursues the insight that large language models (LLMs) trained...
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06/22/2021
Towards Consistent Predictive Confidence through Fitted Ensembles
Deep neural networks are behind many of the recent successes in machine ...
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05/27/2020
Synthetic Petri Dish: A Novel Surrogate Model for Rapid Architecture Search
Neural Architecture Search (NAS) explores a large space of architectural...
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04/27/2020
First return then explore
The promise of reinforcement learning is to solve complex sequential dec...
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03/25/2020
Fiber: A Platform for Efficient Development and Distributed Training for Reinforcement Learning and Population-Based Methods
Recent advances in machine learning are consistently enabled by increasi...
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03/19/2020
Enhanced POET: Open-Ended Reinforcement Learning through Unbounded Invention of Learning Challenges and their Solutions
Creating open-ended algorithms, which generate their own never-ending st...
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02/24/2020
Backpropamine: training self-modifying neural networks with differentiable neuromodulated plasticity
The impressive lifelong learning in animal brains is primarily enabled b...
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02/21/2020
Learning to Continually Learn
Continual lifelong learning requires an agent or model to learn many seq...
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12/29/2019
Improving Deep Neuroevolution via Deep Innovation Protection
Evolutionary-based optimization approaches have recently shown promising...
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12/17/2019
Generative Teaching Networks: Accelerating Neural Architecture Search by Learning to Generate Synthetic Training Data
This paper investigates the intriguing question of whether we can create...
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09/10/2019
An Overview of Open-Ended Evolution: Editorial Introduction to the Open-Ended Evolution II Special Issue
Nature's spectacular inventiveness, reflected in the enormous diversity ...
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07/13/2019
Evolvability ES: Scalable and Direct Optimization of Evolvability
Designing evolutionary algorithms capable of uncovering highly evolvable...
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04/28/2019
Deep Neuroevolution of Recurrent and Discrete World Models
Neural architectures inspired by our own human cognitive system, such as...
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01/30/2019
Go-Explore: a New Approach for Hard-Exploration Problems
A grand challenge in reinforcement learning is intelligent exploration, ...
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01/07/2019
Paired Open-Ended Trailblazer (POET): Endlessly Generating Increasingly Complex and Diverse Learning Environments and Their Solutions
While the history of machine learning so far encompasses a series of pro...
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05/03/2018
VINE: An Open Source Interactive Data Visualization Tool for Neuroevolution
Recent advances in deep neuroevolution have demonstrated that evolutiona...
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04/06/2018
Differentiable plasticity: training plastic neural networks with backpropagation
How can we build agents that keep learning from experience, quickly and ...
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03/09/2018
The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities
Biological evolution provides a creative fount of complex and subtle ada...
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12/18/2017
ES Is More Than Just a Traditional Finite-Difference Approximator
An evolution strategy (ES) variant recently attracted significant attent...
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12/18/2017
Deep Neuroevolution: Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning
Deep artificial neural networks (DNNs) are typically trained via gradien...
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12/18/2017
On the Relationship Between the OpenAI Evolution Strategy and Stochastic Gradient Descent
Because stochastic gradient descent (SGD) has shown promise optimizing n...
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12/18/2017
Safe Mutations for Deep and Recurrent Neural Networks through Output Gradients
While neuroevolution (evolving neural networks) has a successful track r...
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12/18/2017
Improving Exploration in Evolution Strategies for Deep Reinforcement Learning via a Population of Novelty-Seeking Agents
Evolution strategies (ES) are a family of black-box optimization algorit...
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04/17/2017
The Emergence of Canalization and Evolvability in an Open-Ended, Interactive Evolutionary System
Natural evolution has produced a tremendous diversity of functional orga...
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03/30/2017
Born to Learn: the Inspiration, Progress, and Future of Evolved Plastic Artificial Neural Networks
Biological plastic neural networks are systems of extraordinary computat...
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09/07/2016
Fitted Learning: Models with Awareness of their Limits
Though deep learning has pushed the boundaries of classification forward...
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07/11/2014
A Proposed Infrastructure for Adding Online Interaction to Any Evolutionary Domain
To address the difficulty of creating online collaborative evolutionary ...
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06/06/2014
Unsupervised Feature Learning through Divergent Discriminative Feature Accumulation
Unlike unsupervised approaches such as autoencoders that learn to recons...
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02/05/2013
Evolvability Is Inevitable: Increasing Evolvability Without the Pressure to Adapt
Why evolvability appears to have increased over evolutionary time is an ...
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07/28/2012
