IRL VS imitation

Compare IRL vs imitation and see what are their differences.

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IRL imitation
1 1
1 1,138
- 1.8%
0.0 7.5
almost 3 years ago about 2 months ago
Python Python
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

IRL

Posts with mentions or reviews of IRL. We have used some of these posts to build our list of alternatives and similar projects.

imitation

Posts with mentions or reviews of imitation. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing IRL and imitation you can also consider the following projects:

rlalgorithms-tf2 - Packaged deep reinforcement learning algorithms in tensorflow 2.x

neat - [ICCV'21] NEAT: Neural Attention Fields for End-to-End Autonomous Driving

DeepRL-TensorFlow2 - 🐋 Simple implementations of various popular Deep Reinforcement Learning algorithms using TensorFlow2

DI-engine - OpenDILab Decision AI Engine

babyai - BabyAI platform. A testbed for training agents to understand and execute language commands.

f-IRL - Inverse Reinforcement Learning via State Marginal Matching, CoRL 2020

DI-drive - Decision Intelligence Platform for Autonomous Driving simulation.

tianshou - An elegant PyTorch deep reinforcement learning library.

falken - Falken provides developers with a service that allows them to train AI that can play their games