imitation
f-IRL
imitation | f-IRL | |
---|---|---|
1 | 2 | |
1,151 | 35 | |
3.0% | - | |
7.5 | 1.8 | |
2 months ago | 10 months ago | |
Python | Python | |
MIT License | MIT License |
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imitation
f-IRL
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Can you use the reward learned in generative adversarial imitation learning in order to train from scratch?
Code for https://arxiv.org/abs/2011.04709 found: https://github.com/twni2016/f-IRL
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How to pretrain a model on expert data?
Try using an imitation learning algorithm. Two popular options are MaxEnt IRL and GAIL. This repository has GAIL implementation and this repository has MaxEnt IRL and GAIL implementation. There are other implementations too that you can check out.
What are some alternatives?
neat - [ICCV'21] NEAT: Neural Attention Fields for End-to-End Autonomous Driving
Meta-SAC - Auto-tune the Entropy Temperature of Soft Actor-Critic via Metagradient - 7th ICML AutoML workshop 2020
IRL - Algorithms for Inverse Reinforcement Learning
falken - Falken provides developers with a service that allows them to train AI that can play their games
DI-engine - OpenDILab Decision AI Engine
ElegantRL - Massively Parallel Deep Reinforcement Learning. 🔥
babyai - BabyAI platform. A testbed for training agents to understand and execute language commands.
eirli - An Empirical Investigation of Representation Learning for Imitation (EIRLI), NeurIPS'21
DI-drive - Decision Intelligence Platform for Autonomous Driving simulation.
tianshou - An elegant PyTorch deep reinforcement learning library.