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Text comprehension and the computational mind-agencies

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Abstract

Guided by a polymath approach—encompassing neuroscience, philosophy, psychology and computer science, this article describes a novel ‘cognitive’ computational mind framework for text comprehension in terms of Minsky’s ‘Society of Mind’ and ‘Emotion Machine’ theories. Observing a top-down design method, we enumerate here the macrocosmic elements of the model—the ‘agencies’ and memory constructs, followed by an elucidation on the working principles and synthesis concerns. Besides corroboration of results of a dry-run test by thoughts generated by random human subjects; the completeness of the conceptualized framework has been validated as a consequence of its total representation of ‘text understanding’ functions of the human brain, types of human memory and emulation of the layers of the mind. A brief conceptual comparison, between the architecture and existing ‘conscious’ agents, has been included as well. The framework, though observed here in its capacity as a text comprehender, is capable of understanding in general. A cognitive model of text comprehension, besides contributing to the ‘thinking machines’ research enterprise, is envisioned to be strategic in the design of intelligent plagiarism checkers, literature genre-cataloguers, differential diagnosis systems, and educational aids for children with reading disorders. Turing’s landmark 1950 article on computational intelligence is the principal motivator behind our research initiative.

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Acknowledgments

This project is being carried out under the guidance of Professor Sankar K. Pal who is an INAE Chair Professor and J.C. Bose Fellow of the Government of India. The authors acknowledge Alan Turing as the prime inspiration for the work described herein.

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  1. Center for Soft Computing Research, Indian Statistical Institute, Kolkata, India

    Romi Banerjee & Sankar K. Pal

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  1. Romi Banerjee
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Correspondence to Romi Banerjee.

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Banerjee, R., Pal, S.K. Text comprehension and the computational mind-agencies. Nat Comput 14, 603–635 (2015). https://doi.org/10.1007/s11047-014-9478-x

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