Conceptual Mind and Computing Paradigm: A = (f(m), I)

ISBN-13: 9780615862552 / Angielski / Miękka / 2013 / 436 str.

MR Al Galvis

Opis

The conceptual mind represents the pinnacle of natural creation, designed for a single purpose or function: processing of information. Computer systems are information processors, like our minds. In consequence, computer systems can be significantly improved by mirroring the conceptual paradigm and model leveraged by the natural mind. Concepts can be employed to represent all aspects of reality. They can also be applied to communicate ideas, learn, understand, and efficiently solve arbitrary problems. Information is the fundamental abstraction that defines our perceived reality. Conceptually, the natural mind is an entity of beautiful and mathematical simplicity. Only three concepts are involved as part of the mind's 'computing model': a) Information machine (mind itself). b) Single function expressed by the information primitive (f(m)). c) Information represented by a single Concept construct (I). The aforementioned abstractions also represent a streamlined and complete set of natural concepts applicable to the comprehensive implementation of arbitrary information processes and technologies - including cognitive processes like memorizing, learning, logical reasoning, and natural language processing. Messaging is ubiquitous. Realistically, it also represents the only mechanism of communication between the mind and its environment. Information comes in the form of messages (m) which are processed via the primitive (f(m)) - like a sentence, for instance. The conceptual engine (A) that mimics the mind can be expressed mathematically as A = (f (m), I). Information (I) consists of the collection of concepts already known (learned) by the engine. A is fully implementable, and features the same processing power of a computer (Turing complete). As a consequence of the proposed paradigm based on natural concepts and associated computing model, software engineering processes are improved in terms of overall complexity, level of abstraction, true correspondence with reality (Realism), cognitive abilities, interoperability, quality, cost, timeframe, and so forth. The book contains several production-quality applications and examples that illustrate the applicability of the proposed paradigm.