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bandit-learning
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Code and datasets for the Tsetlin Machine
Implements the Tsetlin Machine, Convolutional Tsetlin Machine, Regression Tsetlin Machine, Weighted Tsetlin Machine, and Embedding Tsetlin Machine, with support for continuous features, multigranularity, clause indexing, and literal budget
Contextual Bandits in R - simulation and evaluation of Multi-Armed Bandit Policies
A checkers reinforcement learning AI, and all the tools needed to train it.
Tutorial on the Convolutional Tsetlin Machine
Multi-threaded implementation of the Tsetlin Machine, Convolutional Tsetlin Machine, Regression Tsetlin Machine, and Weighted Tsetlin Machine, with support for continuous features and multigranularity.
Contextual bandit algorithm called LinUCB / Linear Upper Confidence Bounds as proposed by Li, Langford and Schapire
Privacy-Preserving Bandits (MLSys'20)
Some visualizations of bandit algorithm outputs.
Client that handles the administration of StreamingBandit online, or straight from your desktop. Setup and run streaming (contextual) bandit experiments in your browser.
Based on Gentile-Li-Zapella article "Online Clustering of Bandits"
Simple Implementations of Bandit Algorithms in python
A policy gradient approach to a multi-armed bandit problem
This presentation contains very precise yet detailed explanation of concepts of a very interesting topic -- Reinforcement Learning.
Implementing RL algorithms
Detailed solution of solving wargames of over the wire which includes bandit and in future many more.