OpenDILab Decision AI Engine
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Updated
May 24, 2024 - Python
OpenDILab Decision AI Engine
Implementations of selected inverse reinforcement learning algorithms.
Clean PyTorch implementations of imitation and reward learning algorithms
Implementation of Inverse Reinforcement Learning (IRL) algorithms in Python/Tensorflow. Deep MaxEnt, MaxEnt, LPIRL
Master classic RL, deep RL, distributional RL, inverse RL, and more using OpenAI Gym and TensorFlow with extensive Math
TensorFlow2 Reinforcement Learning
Personal notes about scientific and research works on "Decision-Making for Autonomous Driving"
DI-engine docs (Chinese and English)
Maximum Entropy and Maximum Causal Entropy Inverse Reinforcement Learning Implementation in Python
Tensorflow implementation of generative adversarial imitation learning
Implementation of Inverse Reinforcement Learning Algorithm on a toy car in a 2D world problem, (Apprenticeship Learning via Inverse Reinforcement Learning Abbeel & Ng, 2004)
A selection of state-of-the-art research materials on decision making and motion planning.
[T-ITS] Driving Behavior Modeling using Naturalistic Human Driving Data with Inverse Reinforcement Learning
Code for the ACL paper "No Metrics Are Perfect: Adversarial Reward Learning for Visual Storytelling"
(NeurIPS '21 Spotlight) IQ-Learn: Inverse Q-Learning for Imitation
Tensorflow implementation of Generative Adversarial Imitation Learning(GAIL) with discrete action
DESIRE: Distant Future Prediction in Dynamic Scenes with Interacting Agents
Predicting Goal-directed Human Attention Using Inverse Reinforcement Learning (CVPR2020)
A unified end-to-end learning and control framework that is able to learn a (neural) control objective function, dynamics equation, control policy, or/and optimal trajectory in a control system.
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