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            Index to items provided below

  • Hecht-Nielsen R (3 May 2007 talk at Cognitive Computing 2007)  video available at  http://CognitiveComputing2007.berkeley.edu

  • Hecht-Nielsen R (2007) Confabulation Theory. Springer-Verlag

  • Hecht-Nielsen R (2005) Cogent confabulation. Neural Networks 18:111-115

  • R. Hecht-Nielsen R (2004) Perceptrons. UCSD Institute for Neural Computation, Report No. 0403

  • Sagi B et al. (2001)  A biologically motivated solution to the cocktail party problem. Neural Computation 13:1575-1602

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           Links to publications

 

  • Hecht-Nielsen R (2007) Confabulation Theory. Springer-Verlag

Cover:

 

Book description from the back cover:

Confabulation Theory

Confabulation theory offers the first complete detailed explanation of the mechanism of cognition, i.e., thinking, an essential information processing capability of all enbrained Earth animals (bees, octopi, trout, ravens, humans, et al.). Concentrating on the human case, this book offers an hypothesis for the neuronal implementation of cognition, and explores the mathematics and methods of application of its mechanism. Thinking turns out to be starkly alien in comparison with all known technological approaches to information processing. While probably not yet scientifically testable, confabulation theory seems consistent with the facts of neuroscience. Beyond science, any complete detailed explanation of cognition can be investigated by applying it technologically. Multiple experiments of this nature are described in this book in complete detail. The results suggest that confabulation theory can provide the universal platform for building intelligent machines. In short, this book explains how thinking works and establishes the foundation for building machines that think. With two DVDs of courseware, this book is suitable both as a text for professional self-study and for graduate and advanced undergraduate courses in neuroscience, computational intelligence, cognitive science, linguistics and psychology, the prerequisites being elementary mathematics and neuroscience. Because of the theory’s implications for philosophy, education, medicine, anthropology and social science, this book will also be of interest to scientists in those domains.

 

Summary of book content:

Content of the Book

The content of the eight chapters and two DVDs of this book is briefly surveyed

below:

    Chapter 1: Introduction

An introductory overview of confabulation theory: comments on some of the

theory’s possible implications and presentation of this overview of the book’s

contents.

    Chapter 2: Video Presentation Viewcells

The viewcells used in the book’s DVD video presentation are presented. To

help with understanding and retention of the material, each of these should

be referred to while it is being presented during the video.

    Chapter 3: The Mathematics of Cognition

An introduction to the mathematics of confabulation theory. Comments on

the relationship between cogency maximization and Bayesian analysis. An

extensive discussion of the status of confabulation neuroscience. Comments

on the origins of confabulation theory.

    Chapter 4: Cogent Confabulation

Mathematical foundations of confabulation theory are presented, including

statement and proof of the Fundamental Theorem of Cognition and the theorem

showing that cogent confabulation within a logical information environment

yields Aristotelian logic. Computer experiments with a single confabulation

are presented, with all details provided. Replication of these single

confabulation experiments is the logical starting point for those wanting to

gain hands-on experience with confabulation architectures.

    Chapter 5: Confabulation Neuroscience I

A concise overview of confabulation neuroscience. This material is prerequisite

for Chap. 6.

    Chapter 6: The Mechanism of Thought

Computer experiments with multiconfabulation are presented, with all details.

These sentence continuation experiments illustrate that thinking is exactly

like moving. Replication of these multiconfabulation experiments is the

second logical step for those wishing to gain hands-on experience with confabulation

architectures.

    Chapter 7: Mechanization of Confabulation

Further details of confabulation architecture design and implementation are

presented. Approaches for application of confabulation architectures to language,

vision, and hearing are discussed in some detail.

    Chapter 8: Confabulation Neuroscience II

An expanded discussion of confabulation neuroscience.

    DVDs

The book’s two DVDs (provided in pouches inside the front and back covers of the book) contain the following material:

1. The Mechanism of Thought video presentation (Part I on DVD Disk 1 and

Part II on DVD Disk 2).

2. PDF file of the Viewcells used in The Mechanism of Thought video presentation.

This computer-readable file is included on both Disk 1 and Disk 2.

3. PDF file of the Presentation Notes for The Mechanism of Thought video

presentation.

 

Confabulation Theory can be purchased from:

Springer.com (  http://www.springer.com/west/home?SGWID=4-102-22-173707346-0&changeHeader=true  )

or

Amazon.com (  http://www.amazon.com/gp/product/3540496033  )

or any bookstore

 

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  • Hecht-Nielsen R (2005) Cogent confabulation. Neural Networks 18:111-115

This paper establishes the fundamental mathematics of animal thought.  It shows that, in a logical ‘Aristotelian’ information environment, thinking automatically yields the same results as logic.  The Fundamental Theorem of Animal Cognition is stated and proven.  This theorem bridges the gap between the ideal information processing operation of thinking (cogency maximization) and the biologically implementable information processing operation, confabulation.

 

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  • R. Hecht-Nielsen R (2004) Perceptrons. UCSD Institute for Neural Computation, Report No. 0403

This monograph surveys perceptrons, including the general formulation, mathematical theory, training methodologies, and associated topics.  An overview of the history of the subject including photographs of Frank Rosenblatt and his original Perceptron machine is included.  This document has been used a number of times as a text for an introductory neural networks course at UCSD.

 

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  • Sagi B et al. (2001)  A biologically motivated solution to the cocktail party problem. Neural Computation 13:1575-1602

This was the first research report employing constructs from what is now confabulation theory. The cocktail party processor evaluated in this research demonstrated the ability to attend correctly to one speechstream in a ‘single microphone’ mixture of FIVE speechstreams. The speechstream to be attended to started slightly before the other four – to give the processor time to get its recognition processes running. Then the other streams were all added. Remarkably, each of the speakers was the same person – just reading different passages of text; and each speechstream had the same volume level. Because this cocktail party processor did not use multiple microphones (as do almost all others) and did not employ blind source separation / ICA processing; comparing these spectacular results with one microphone with the capabilities of many-microphone systems is not easy – and so this research has been largely ignored (although it is sometimes cited among ‘other cocktail party problem methods that will not be discussed here’). Nonetheless, the technical approach explored in this research seems capable of providing a robust solution to a wide variety of practical cocktail party problems (i.e., various scenarios in which one speaker’s voice output is to be understood, even though their speech signal is mixed in with a variety of other transient soundstreams, including other people’s voices, in a single microphone signal).

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