Tabular methods for reinforcement learning
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Updated
Jul 3, 2020 - Python
Tabular methods for reinforcement learning
A comprehensive toolkit and benchmark for tabular data learning, featuring over 20 deep methods, more than 10 classical methods, and 300 diverse tabular datasets.
Source for the sample efficient tabular RL submission to the 2019 NIPS workshop on Biological and Artificial RL
Implementations of various RL and Deep RL algorithms in TensorFlow, PyTorch and Keras.
[ICML 2024] BiSHop: Bi-Directional Cellular Learning for Tabular Data with Generalized Sparse Modern Hopfield Model
Code examples for simple reinforcement learning projects
An investigation into tabular classification with deep NNs for ETHZ Machine Learning for Healthcare on the MIT-BIH arrythmia dataset .
Modular Names Classifier, Object Oriented PyTorch Model
R.L. methods and techniques.
The implementation of tabular solution methods in Reinformcement Learning, Sutton's book: Part I
Revisiting tabular and deep reinforcement learning methods.
This is a python script file that translates tree-graph information stored in a .txt file to complicated LaTeX code, which can be compiled into a pretty tree graph in LaTeX editor (ex. Overleaf).
Implementation of tabular methods for Reinforcement learning
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