Pytorch code for ICLR-20 Paper "Learning to Explore using Active Neural SLAM"

CURL: Contrastive Unsupervised Representation Learning for Sample-Efficient Reinforcement Learning

Pytorch code for NeurIPS-20 Paper "Object Goal Navigation using Goal-Oriented Semantic Exploration"

✨ A plotter for reinforcement learning (RL)

Accelerated minigrid environments with JAX

OpenAI团队的深度强化学习教程中文版

Recall to Imagine, a model-based RL algorithm with superhuman memory. Oral (1.2%) @ ICLR 2024

Codes accompanying the paper "Believe What You See: Implicit Constraint Approach for Offline Multi-Agent Reinforcement Learning" (NeurIPS 2021 Spotlight https://arxiv.org/abs/2106.03400)

A reusable framework for successor features for transfer in deep reinforcement learning using keras.

Mirror Descent Policy Optimization

A general model-free off-policy actor-critic implementation. Continuous and Discrete Soft Actor-Critic with multimodal observations, data augmentation, offline learning and behavioral cloning.

OpenAI团队的深度强化学习教程中文版

This repository implements the use of AI for robot tasks.

Deep Reinforcement Learning framework based on TensorFlow and OpenAI Gym

Synthesizing safe robot policies in joint physical-belief spaces with deep RL! - CoRL 2023

RLbox: Solving OpenAI Gym with TensorFlow

Code for NeurIPS 2023 paper Accountability in Offline Reinforcement Learning: Explaining Decisions with a Corpus of Examples

Yet another deep reinforcement learning

Ensemble and Auxiliary Tasks for Data-Efficient Deep Reinforcement Learning

Exploration of deep reinforcement learning and various state-of-the-art techniques to create a turely autonomous agent.