Human Intellect and Cognitive Science: Toward a General Unified Theory of Intelligence

Human Intellect and Cognitive Science: Toward a General Unified Theory of Intelligence

Human Intellect and Cognitive Science: Toward a General Unified Theory of Intelligence

Human Intellect and Cognitive Science: Toward a General Unified Theory of Intelligence

Synopsis

The advancement of knowledge concerning the complexities of human intellective processes can best be achieved by combining theory and research from the disciplines of cognitive psychology and artificial intelligence. Wagman explores various aspects of these disciplines to further his ideas. He examines the nature of the human intellect and proposes a theory of representation and intelligence that is applicable to human, computer, and animal cognition. He also evaluates theory and research concerned with structure and process in human reasoning and human problem solving. Several scientific discovery systems including BACON, FARENHEIT, and IDS are described in depth. The ability of these systems to emulate solutions to 10 types of scientific problems is examined. The capacity theory of language comprehension is also presented and extended to the domain of cognitive processes.

Excerpt

The study of thinking occupies a central place in cognitive psychology and artificial intelligence. These disciplines employ a range of methods that include computational problem-solving systems, computer models of human reasoning and problem solving, and traditional laboratory experiments with human subjects that do not utilize computational modeling. This book examines the nature of thinking from the perspective of these theoretical and research approaches.

In the first chapter, the nature of representation and its relationship to knowledge and to theory of mind are examined. The complex concept of knowledge representation is decomposed into its surrogate, ontological, reasoning, computational, and communication aspects. A general theory of intelligence and representation applicable to animal, human, and computer cognition is developed.

In the second chapter, theory and research concerned with the processes of human reasoning are examined. A formal core theory of plausible reasoning is described, and relevant empirical protocol evidence is presented. The use of abstract rules in reasoning is analyzed and compared with instance models in both symbolic and connectionist architectures.

In the third chapter, theory and research concerned with human problem solving are described in depth. Intuitive problem solving in the context of discovery and verification is discussed. Experiments on the role of intuition in the discovery process are described. Theory and research concerned with the central importance of problem representation in insightful problem solving are presented. The SWITCH computer program provides a sufficiency emulation of the experimental data and the essential human problem-solving heuristics.

In the fourth chapter, artificial-intelligence approaches to scientific discovery are described. The concepts, methods, and results of several scientific discovery systems including BACON, FAHRENHEIT, and IDS are described in depth, and their strengths and weaknesses are . . .

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