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07/05/2023
First-Explore, then Exploit: Meta-Learning Intelligent Exploration
Standard reinforcement learning (RL) agents never intelligently explore ...
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06/02/2023
OMNI: Open-endedness via Models of human Notions of Interestingness
Open-ended algorithms aim to learn new, interesting behaviors forever. T...
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06/01/2023
Thought Cloning: Learning to Think while Acting by Imitating Human Thinking
Language is often considered a key aspect of human thinking, providing u...
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06/23/2022
Video PreTraining (VPT): Learning to Act by Watching Unlabeled Online Videos
Pretraining on noisy, internet-scale datasets has been heavily studied a...
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08/26/2021
Continual learning under domain transfer with sparse synaptic bursting
Existing machines are functionally specific tools that were made for eas...
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06/28/2021
Multi-task curriculum learning in a complex, visual, hard-exploration domain: Minecraft
An important challenge in reinforcement learning is training agents that...
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06/12/2020
Open Questions in Creating Safe Open-ended AI: Tensions Between Control and Creativity
Artificial life originated and has long studied the topic of open-ended ...
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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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03/03/2020
Scaling MAP-Elites to Deep Neuroevolution
Quality-Diversity (QD) algorithms, and MAP-Elites (ME) in particular, ha...
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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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12/17/2019
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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10/22/2019
A deep active learning system for species identification and counting in camera trap images
Biodiversity conservation depends on accurate, up-to-date information ab...
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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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05/27/2019
AI-GAs: AI-generating algorithms, an alternate paradigm for producing general artificial intelligence
Perhaps the most ambitious scientific quest in human history is the crea...
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04/18/2019
Understanding Neural Networks via Feature Visualization: A survey
A neuroscience method to understanding the brain is to find and study th...
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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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12/27/2018
Robustness to Out-of-Distribution Inputs via Task-Aware Generative Uncertainty
Deep learning provides a powerful tool for machine perception when the o...
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12/17/2018
An Atari Model Zoo for Analyzing, Visualizing, and Comparing Deep Reinforcement Learning Agents
Much human and computational effort has aimed to improve how deep reinfo...
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07/09/2018
Evolving Multimodal Robot Behavior via Many Stepping Stones with the Combinatorial Multi-Objective Evolutionary Algorithm
An important challenge in reinforcement learning, including evolutionary...
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06/01/2018
Deep Curiosity Search: Intra-Life Exploration Improves Performance on Challenging Deep Reinforcement Learning Problems
Traditional exploration methods in RL require agents to perform random a...
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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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05/20/2017
Diffusion-based neuromodulation can eliminate catastrophic forgetting in simple neural networks
A long-term goal of AI is to produce agents that can learn a diversity o...
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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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03/16/2017
Automatically identifying, counting, and describing wild animals in camera-trap images with deep learning
Having accurate, detailed, and up-to-date information about the location...
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11/30/2016
Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space
Generating high-resolution, photo-realistic images has been a long-stand...
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05/30/2016
Synthesizing the preferred inputs for neurons in neural networks via deep generator networks
Deep neural networks (DNNs) have demonstrated state-of-the-art results o...
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02/11/2016
Multifaceted Feature Visualization: Uncovering the Different Types of Features Learned By Each Neuron in Deep Neural Networks
We can better understand deep neural networks by identifying which featu...
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11/24/2015
Convergent Learning: Do different neural networks learn the same representations?
Recent success in training deep neural networks have prompted active inv...
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06/22/2015
Understanding Neural Networks Through Deep Visualization
Recent years have produced great advances in training large, deep neural...
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05/23/2015
The evolutionary origins of hierarchy
Hierarchical organization -- the recursive composition of sub-modules --...
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04/20/2015
Illuminating search spaces by mapping elites
Many fields use search algorithms, which automatically explore a search ...
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12/05/2014
Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images
Deep neural networks (DNNs) have recently been achieving state-of-the-ar...
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11/06/2014
How transferable are features in deep neural networks?
Many deep neural networks trained on natural images exhibit a curious ph...
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07/13/2014
Robots that can adapt like animals
As robots leave the controlled environments of factories to autonomously...
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04/17/2013
Hands-free Evolution of 3D-printable Objects via Eye Tracking
Interactive evolution has shown the potential to create amazing and comp...
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07/11/2012