Walkthroughs for DSL, AirSim, the Vector Institute, and more
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Updated
Mar 31, 2022 - C++
Walkthroughs for DSL, AirSim, the Vector Institute, and more
a modular reinforcement learning library with JAX agents
💡 Grasp - Pick-and-place with a robotic hand 👨🏻💻
Simple implementations of Cartesian Genetic Programming (CGP) and Linear Genetic Programming (LGP) in JAX
Learning to Generalize towards Unseen Domains via a Content-Aware Style Invariant Framework for Disease Detection from Chest X-rays
An implementation of Short Horizon Actor Critic writen in Jax. Core algorithm written in the style of Brax, with several bits taken from Xu's original paper.
Relentlessly learning, persistently failing, but never surrendering.
The Simple Simulator: Simulation Made Simple
Procedural Environment Generation for Accelerated Multi-Agent Reinforcement Learning
GPU-accelerated Evolutionary Multiobjective Optimization Using Tensorized RVEA.
[ICML 2024] Official environments and JAX-implementations for "Subequivariant Reinforcement Learning in 3D Multi-Entity Physical Environments"
GPU-accelerated NeuroEvolution of Augmenting Topologies (NEAT)
Distributed GPU-Accelerated Framework for Evolutionary Computation. Comprehensive Library of Evolutionary Algorithms & Benchmark Problems.
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