AI, granular computing, and automata with structured memory

Authors:
Mark Burgin;Allen Klinger
Affiliations:
Department of Computer Science, University of California, Los Angeles, Los Angeles, CA;Department of Computer Science, University of California, Los Angeles, Los Angeles, CA
Venue:
DNCOCO'09 Proceedings of the 8th WSEAS international conference on Data networks, communications, computers
Year:
2009

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Abstract

Examining artificial intelligence (AI) problems with the aid of a granular-computing mathematical model. The model is based on Turing machines and recursive algorithms. Through extension to inductive Turing machines, we add super-recursive algorithms enhanced with structured memory to these situations. We consider such AI problems as machine learning, text recognition and advanced computation in the context of granular computational models. Using the elaborated model, we demonstrate that granulation gives a powerful means for learning and computing. The paper shows that it provides both for increasing efficiency of computation and for extending the scope of what is computable, decidable and learnable information.