Tsetlin machine

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A Tsetlin machine is a form of learning automaton based upon algorithms from reinforcement learning to learn expressions from propositional logic. Ole-Christoffer Granmo gave the method its name after Michael Lvovitch Tsetlin and his Tsetlin automata. The method uses computationally simpler and more efficient primitives compared to more ordinary artificial neural networks, but while the method may be faster it has a steep drop in signal-to-noise ratio as the signal space increases.[1]

As of April 2018 it has shown promising results on a number of test sets.[2][3]

References[edit]

  1. ^ Granmo, Ole-Christoffer (2018-04-04). "The Tsetlin Machine - A Game Theoretic Bandit Driven Approach to Optimal Pattern Recognition with Propositional Logic". arXiv:1804.01508 [cs.AI].
  2. ^ Christiansen, Atle. "The Tsetlin Machine outperforms neural networks - Center for Artificial Intelligence Research". cair.uia.no. Retrieved 2018-05-03.
  3. ^ Øyvann, Stig. "AI-gjennombrudd i Agder | Computerworld". Computerworld (in Norwegian). Retrieved 2018-05-04.