Tutorials, assignments, and competitions for MIT Deep Learning related courses.

DeepTraffic is a deep reinforcement learning competition, part of the MIT Deep Learning series.

A curated list of awesome Deep Reinforcement Learning resources.

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"

:sparkles: A plotter for reinforcement learning (RL)

VR-Caps: A Virtual Environment for Active Capsule Endoscopy

Accelerated minigrid environments with JAX

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.

A UCI-compatible four-player chess engine

You can see a reference for Books, Articles, Courses and Educational Materials in this field. Implementation of Reinforcement Learning Algorithms and Environments. Python, OpenAI Gym, Tensorflow.

Code repository with classical reinforcement learning and deep reinforcement learning methods for Pokémon battles in Pokémon Showdown.

This repository implements the use of AI for robot tasks.

Deep Reinforcement Learning framework based on TensorFlow and OpenAI Gym

No description provided.

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

Implementation of Curiosity-Driven Exploration with PyTorch

RLbox: Solving OpenAI Gym with TensorFlow

Attend Before you Act: Leveraging human visual attention for continual learning

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

DRLA-eTGM

A curated list of awesome intelligent autonomous systems ecosystem

Yet another deep reinforcement learning

A JAX framework for differentiable neuromechanical flight optimization. Unifies neural CPG, articulated body dynamics, and unsteady aerodynamics to synthesize Lyapunov-stable insect flight.

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