Chemical AI is chemically synthesized artificial intelligence that has the ability of learning in addition to information processing. A research project on chemical AI, called the Molecular Cybernetics Project, was launched in Japan in 2021 with the goal of creating a molecular machine that can learn a type of conditioned reflex through the process called classical conditioning. If the project succeeds in developing such a molecular machine, the next step would be to configure a network of such machines to realize more complex functions. With this motivation, this paper develops a method for learning a desired function in the network of nodes each of which can implement classical conditioning. First, we present a model of classical conditioning, which is called here a classical conditioning gate. We then propose a learning algorithm for the network of classical conditioning gates.
@article{arxiv.2312.15161,
title = {Networks of Classical Conditioning Gates and Their Learning},
author = {Shun-ichi Azuma and Dai Takakura and Ryo Ariizumi and Toru Asai},
journal= {arXiv preprint arXiv:2312.15161},
year = {2023}
}