OpenDILab Decision AI Engine
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Updated
Jun 13, 2024 - Python
OpenDILab Decision AI Engine
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
Library for Model Based RL
Code to reproduce the experiments in Sample Efficient Reinforcement Learning via Model-Ensemble Exploration and Exploitation (MEEE).
DI-engine docs (Chinese and English)
Unofficial Pytorch code for "Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models"
Unofficial Implementation of the paper "Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control", applied to gym environments
Model-based Reinforcement Learning Framework
Code release for Efficient Planning in a Compact Latent Action Space (ICLR2023) https://arxiv.org/abs/2208.10291.
Deep active inference agents using Monte-Carlo methods
Latent Imagination Facilitates Zero-Shot Transfer in Autonomous Racing
Code for "World Model as a Graph: Learning Latent Landmarks for Planning" (ICML 2021 Long Presentation)
Adaptable tools to make reinforcement learning and evolutionary computation algorithms.
Model-based reinforcement learning in TensorFlow
An implementation of MuZero in JAX.
Recall to Imagine, a model-based RL algorithm with superhuman memory. Oral (1.2%) @ ICLR 2024
A number of agents (PPO, MuZero) with a Perceiver-based NN architecture that can be trained to achieve goals in nethack/minihack environments.
Official repo for "iVideoGPT: Interactive VideoGPTs are Scalable World Models", https://arxiv.org/abs/2405.15223
The Hierarchical Intrinsically Motivated Agent (HIMA) is an algorithm that is intended to exhibit an adaptive goal-directed behavior using neurophysiological models of the neocortex, basal ganglia, and thalamus.
LAMBDA is a model-based reinforcement learning agent that uses Bayesian world models for safe policy optimization
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