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[2L4-GS-1-02] Logical reasoning using graphical networks and its refinement using category theory
Keywords:category theory, logical reasoning, database, graph
Vast progresses are seen in neural-network based artificial intelligences. However, limitations are pointed out concerning their abilities of logical reasoning. This research presents a framework for logical reasoning using graphical networks: cognitive-logs. Cognitive-logs is a set of databases where the main elements are “actions” represented by verbs in natural languages and “participants” who perform the actions. The construction of cognitive-logs refers cognitive linguistics so that it represents humans cognitive mechanisms. By applying category theory, cognitive-logs flexibly reasons with logical rigors. This presentation illustrates the construction of cognitive-logs and demonstrates the wide applicability of cognitive-logs. Recognizing actions as entities was the key to the construction. Computations into cognitive-logs reproduce theories of cognitive sciences such as prototype theory.
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