Tsetlin Machine-based solution to predict the winner of a Hex board game at different stages. Utilizes graph-based board representations and custom datasets for training.
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Updated
Feb 6, 2025 - Python
Tsetlin Machine-based solution to predict the winner of a Hex board game at different stages. Utilizes graph-based board representations and custom datasets for training.
Code for UiA Learning Systems Course, including Tsetlin Machines and Bayesian Networks. 🧑🔬
Master's Thesis project at University of Agder, Spring 2020. Classification with Tsetlin Machine on board game 'GO'.
Various AIs for the board game hex, including Monte Carlo Tree Search with the Tsetlin Machine
Customer Churn (Drop Off) Modeling
Non-official Tsetlin Machine replication from the original paper. Tsetlin Machine are an interpretable and promising machine learning paradigm to enhance AI transparency.
Code repository for my master thesis experiments.
Master's thesis project, University of Agder, Spring 2020, Checkers game classification by the use of Tsetlin Machine.
Tsetlin Machine-based indoor localization using BLE RSSI fingerprinting.
Efficient parallelized implementation of Multilabel Classifier and Regressor Tsetlin Machines
Demo of tsetlin on the MNIST character data set that uses genetic and multi-threading. Derived from Ole-Christoffer Granmo.
Welcome to the repo for our 2025 UiA Master Thesis - Anomaly Detection in Wind Turbine SCADA Data Using Tsetlin Machine Autoencoder and Classifier 🔬
Portfolio assessment for IKT457 - Learning Systems, Autumn 2025
High-performance Tsetlin Machine in Rust. Const generics, bitwise SIMD, zero-alloc inference. 25-92x faster clause evaluation.
A Golang implementation of the Tsetlin Machine.
Scikit-learn-compatible python3 wrapper for Tsetlini - a Tsetlin Machine learning model
University project in the course ICT Seminar 3. Using Tsetlin Machine for Pattern Recognition in the game Connect Four.
Predicting Win/Loss/Draw on the Connect Four dataset with Tsetlin Machines
A Python framework for N-agent collective learning using Tsetlin Machines and synthetic data sharing, supporting zero-shot sensor onboarding and LLM-driven feature extraction.
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