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Found 5 papers, 3 papers with code
QDax: A Library for Quality-Diversity and Population-based Algorithms with Hardware Acceleration
QDax is an open-source library with a streamlined and modular API for Quality-Diversity (QD) optimization algorithms in Jax.
PASTA: Pretrained Action-State Transformer Agents
Self-supervised learning has brought about a revolutionary paradigm shift in various computing domains, including NLP, vision, and biology.
Jumanji: a Diverse Suite of Scalable Reinforcement Learning Environments in JAX
Open-source reinforcement learning (RL) environments have played a crucial role in driving progress in the development of AI algorithms.
Gradient-Informed Quality Diversity for the Illumination of Discrete Spaces
While early QD algorithms view the objective and descriptor functions as black-box functions, novel tools have been introduced to use gradient information to accelerate the search and improve overall performance of those algorithms over continuous input spaces.
Neuroevolution is a Competitive Alternative to Reinforcement Learning for Skill Discovery
Recent work has shown that training a mixture of policies, as opposed to a single one, that are driven to explore different regions of the state-action space can address this shortcoming by generating a diverse set of behaviors, referred to as skills, that can be collectively used to great effect in adaptation tasks or for hierarchical planning.
