Stars
Simulation platform for general-purpose robotics & embodied AI learning.
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
Collections of robotics environments geared towards benchmarking multi-task and meta reinforcement learning
LUTE = Learning Using Texts: learn languages through reading.
High throughput synchronous and asynchronous reinforcement learning
Aerial Gym Simulator - Isaac Gym Simulator for Aerial Robots
Gym - 32 levels of original Super Mario Bros
A large-scale benchmark for co-optimizing the design and control of soft robots, as seen in NeurIPS 2021.
A Python interface for Minecraft built on gRPC
This program evolves an AI using the NEAT algorithm to play Super Mario Bros.
map elites python reference implementation
Experiment code associated with our paper: "Aerodynamic Design Optimization and Shape Exploration using Generative Adversarial Networks"
A derivative-free solver for general nonlinear optimization.
A modified benchmark for designing and controlling 2D Voxel-based Soft Robots
OpenAI gym environment for evolving morphologies of 2D virtual creatures.
HPO and Architecture Benchmarking for RL: Dynamically, Reactive and Efficient
Repository replicating the design- and behaviour-adaptation algorithm using reinforcement learning algorithm presented in the paper " Data-efficient Co-Adaptation of Morphology and Behaviour with D…
OpenAI Gym environment which reproduces the behaviour of a wind turbine realistically using CCBlade aeroelastic code
Software for Evolving Modular Robots in Unity
Mallows Kendall. A python package to for Mallows Model with top-k and complete rankings using Kendall's-tau distance. By Ahmed Boujaada, Fabien Collas and Ekhine Irurozki. We present methods for in…
Python-based performance analyzer for Iterative Optimization Heuristics.
Minimax Classification under Concept Drift with Multidimensional Adaptation and Performance Guarantees
Capping methods for the automatic configuration of optimization algorithms.