Principles of noology [electronic resource] : toward a theory and science of intelligence / Seng-Beng Ho/
2016
Q335
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Details
Title
Principles of noology [electronic resource] : toward a theory and science of intelligence / Seng-Beng Ho/
Author
Ho, Seng-Beng.
ISBN
9783319321134 (electronic book)
3319321137 (electronic book)
9783319321110
3319321137 (electronic book)
9783319321110
Publication Details
Switzerland : Springer, 2016.
Language
English
Description
1 online resource (444 pages)
Call Number
Q335
Dewey Decimal Classification
006.3
610
610
Summary
The idea of this book is to establish a new scientific discipline, "noology," under which a set of fundamental principles are proposed for the characterization of both naturally occurring and artificial intelligent systems. The methodology adopted in Principles of Noology for the characterization of intelligent systems, or "noological systems," is a computational one, much like that of AI. Many AI devices such as predicate logic representations, search mechanisms, heuristics, and computational learning mechanisms are employed but they are recast in a totally new framework for the characterization of noological systems. The computational approach in this book provides a quantitative and high resolution understanding of noological processes, and at the same time the principles and methodologies formulated are directly implementable in AI systems. In contrast to traditional AI that ignores motivational and affective processes, under the paradigm of noology, motivational and affective processes are central to the functioning of noological systems and their roles in noological processes are elucidated in detailed computational terms. In addition, a number of novel representational and learning mechanisms are proposed, and ample examples and computer simulations are provided to show their applications. These include rapid effective causal learning (a novel learning mechanism that allows an AI/noological system to learn causality with a small number of training instances), learning of scripts that enables knowledge chunking and rapid problem solving, and learning of heuristics that further accelerates problem solving. Semantic grounding allows an AI/noological system to "truly understand" the meaning of the knowledge it encodes. This issue is extensively explored. This is a highly informative book providing novel and deep insights into intelligent systems which is particularly relevant to both researchers and students of AI and the cognitive sciences.
Bibliography, etc. Note
Includes bibliographical references and index.
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Access limited to authorized users.
Source of Description
Description based on print version record.
Series
Socio-Affective Computing ; v. 3
Available in Other Form
Principles of Noology : Toward a Theory and Science of Intelligence
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Table of Contents
Rapid Unsupervised Effective Causal Learning
A General Noological Framework
Conceptual Grounding and Operational Representation
Causal Rules, Problem Solving, and Operational Representation
The Causal Role of Sensory Information
Application to the StarCraft Game Environment
A Grand Challenge for Noology and Computational Intelligence
Affect Driven Noological Processes
Summary and Beyond
Appendix A: Causal vs Reinforcement Learning
Appendix B: Rapid Effective Causal Learning Algorithm.
A General Noological Framework
Conceptual Grounding and Operational Representation
Causal Rules, Problem Solving, and Operational Representation
The Causal Role of Sensory Information
Application to the StarCraft Game Environment
A Grand Challenge for Noology and Computational Intelligence
Affect Driven Noological Processes
Summary and Beyond
Appendix A: Causal vs Reinforcement Learning
Appendix B: Rapid Effective Causal Learning Algorithm.