humancompatibleai Goto Github PK

adversarial-policies

Find best-response to a fixed policy in multi-agent RL

assistance-games

Supporting code for Assistance Games as a Framework paper

atari-irl

baselines

OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

better-adversarial-defenses

Training in bursts for defending against adversarial policies

carla-autoware

Integration of AutoWare AV software with the CARLA simulator

coiltraine

Training framework for conditional imitation learning

cs294-149-fa18-notes

LaTeX Notes from the Fall 2018 version of CS294-149: AGI Safety and Control

deep-rlsp

Code accompanying "Learning What To Do by Simulating the Past", ICLR 2021.

derail

Supporting code for diagnostic seals paper

dmc2gym

OpenAI Gym wrapper for the DeepMind Control Suite

eirli

An Empirical Investigation of Representation Learning for Imitation (EIRLI), NeurIPS'21

evaluating-rewards

Library to compare and evaluate reward functions

gym

A toolkit for developing and comparing reinforcement learning algorithms.

human_ai_robustness

human_aware_rl

Code for "On the Utility of Learning about Humans for Human-AI Coordination"

ilqr

Iterative Linear Quadratic Regulator with auto-differentiatiable dynamics models

imitation

Clean PyTorch implementations of imitation and reward learning algorithms

interactive-behaviour-design

interactive-behaviour-design-baselines

interactive-behaviour-design-basicfetch

interactive-behaviour-design-gym

interpreting-rewards

Experiments in applying interpretability techniques to learned reward functions.

katago-driver-bug-repro

Docker files to help reproduce bug described in https://forums.developer.nvidia.com/t/kernel-oops-null-pointer-dereference-when-closing-cuda-application-katago/211270/3

learning-from-human-preferences

Reproduction of OpenAI and DeepMind's "Deep Reinforcement Learning from Human Preferences"

learning_biases

Infer how suboptimal agents are suboptimal while planning, for example if they are hyperbolic time discounters.

logical-active-classification

Use active learning to classify data represented as boundaries of regions in parameter space where a parametrised logical formula holds.

malmo

Project Malmo is a platform for Artificial Intelligence experimentation and research built on top of Minecraft. We aim to inspire a new generation of research into challenging new problems presented by this unique environment. --- For installation instructions, scroll down to *Getting Started* below, or visit the project page for more information:

minerl

MineRL Competition for Sample Efficient Reinforcement Learning - Python Package

multi-agent