Lists (2)
Stars
[CoRL 2022] InterFuser: Safety-Enhanced Autonomous Driving Using Interpretable Sensor Fusion Transformer
Bayesian optimisation & Reinforcement Learning library developed by Huawei Noah's Ark Lab
Repository for the paper "Verifying Reinforcement Learning up to Inifinity"
nl2spec: Interactively Translating Unstructured Natural Language to Temporal Logics with Large Language Models
High-throughput simulation platform for Artificial Intelligence reseach
A course in reinforcement learning in the wild
VMAS is a vectorized differentiable simulator designed for efficient Multi-Agent Reinforcement Learning benchmarking. It is comprised of a vectorized 2D physics engine written in PyTorch and a set …
Streamlining reinforcement learning with RLOps. State-of-the-art RL algorithms and tools.
Executive control code for STRANDS robots.
One repository is all that is necessary for Multi-agent Reinforcement Learning (MARL)
davexparker / prism
Forked from prismmodelchecker/prismDave's fork of the main development version of the PRISM model checker. http://www.prismmodelchecker.org/
Modularized Implementation of Deep RL Algorithms in PyTorch
[PLDI 19'] An Inductive Synthesis Framework for Verifiable Reinforcement Learning
Risk-Averse Distributional Reinforcement Learning: Code
Basic constrained RL agents used in experiments for the "Benchmarking Safe Exploration in Deep Reinforcement Learning" paper.
An extension of the PyMARL codebase that includes additional algorithms and environment support
From search engines, to science, to robotics, this reposity is meant to showcase the use of reinforcement learning in the world..
This is the official implementation of Multi-Agent PPO (MAPPO).
Markov Decision Processes, Dynamic Programming and Reinforcement Learning
📊 Save matplotlib figures as TikZ/PGFplots for smooth integration into LaTeX.
Code for the paper "AlwaysSafe: Reinforcement Learning Without Safety Constraint Violations During Training"
Code to reproduce results in the AAAI 2018 paper "Efficient Probabilistic Performance Bounds for Inverse Reinforcement Learning" by Daniel S. Brown and Scott Niekum.
Code for CORL'18 paper "Risk-Aware Active Inverse Reinforcement Learning"
uoe-agents / lb-foraging
Forked from semitable/lb-foragingLevel-Based Foraging (LBF): A multi-agent reinforcement learning environment
Level-based Foraging (LBF): A multi-agent environment for RL
Simple and easily configurable grid world environments for reinforcement learning