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Attractor Approach in Modeling Logic in Neural Networks

Student: Daniil Vankov

Supervisor: Andrey A. Gavrilyuk

Faculty: Faculty of Computer Science

Educational Programme: Applied Mathematics and Information Science (Bachelor)

Year of Graduation: 2018

Logical modeling is a set of tasks in machine learning and neuroscience, with the purpose of searching for opportunities to improve artificial intelligence algorithms, a better understanding of the mechanisms of the brain's functioning and the search for interrelations between artificial neural networks and natural ones. The attractor approach is used to classify logical relations in a pair of sentences. With the help of the trained model and the maximization of activation method, an algorithm of logical inference is constructed.

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