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Unified theories of cognition
Newell A., Harvard University Press, Cambridge, MA, 1990. Type: Book (9789780674920996)
Date Reviewed: Jul 1 1991

A unified theory of cognition is defined as a unique set of mechanisms that explains the following elements of cognitive behavior:

  • problem solving, decision making, and routine action

  • memory, learning, and skill

  • language

  • motivation and emotion

  • imagining, dreaming, and daydreaming

The order of items in this list reflects Newell’s view of their importance in cognitive behavior. He views the list as a set of prioritized objectives for the building of a unified theory. This list is as important to a unified theory of cognition as a system of axioms is to a formal theory. Just as there is a place for different sets of axioms, so there are other, justified variations on this list. For example, I would give memory the highest priority, followed by learning and then decision making.

As long as the elements in the list can be explained in different ways, more than one unified theory of cognition can be built from the current state of knowledge. These theories would differ in their level of detail and in how far down the list they would go. This variety is why Newell uses the plural in the title of this book.

The book, based on the 1987 William James lectures delivered by the author at Harvard University, presents an example of a unified cognitive theory. It is based on the problem-solving system Soar, developed by the author and his colleagues. The book contains eight chapters, a bibliography, and name and subject indexes. Chapter 1 is an introduction that discusses unified cognitive theories and ways to build them.

Chapter 2 presents the basic concepts of cognitive systems, including behaving system, knowledge system, computational system, intelligence and intelligent behavior, search in the problem space, and knowledge search. These are the major concepts needed to describe cognitive systems in general.

Chapter 3 discusses the basics of human cognitive architecture. Newell assumes that this architecture is constructed out of neural technology and is capable of intelligent behavior. These assumptions lead to what he calls the real-time constraint on human cognition; the limitations are neural speed and the response time of the cognitive symbol system.

Chapter 4 describes the symbolic processing system Soar, which Newell uses as the basis for a unified theory of cognition in the rest of the book. He pays special attention to Soar’s problem-space structure, production system, decision cycle, and ability to learn using a chunking mechanism. A paragraph discusses a mapping between the Soar architecture and that of the human brain.

The rest of the book deals with Newell’s unified theory of cognition. It contains an overview of different areas of cognitive behavior and attempts to explain them in view of the organization of Soar. Chapter 5 focuses on immediate behavior--tasks that take a second or two from presentation to completion--and on discrete perceptual-motor behavior. Chapter 6 covers a theory of human memory (short- and long-term, declarative and procedural, episodic and semantic), learning, and skill acquisition. Chapter 7 gives an overview of tasks that take minutes or longer. These tasks include problem solving, logical reasoning, and sentence verification.

Chapter 8 discusses which elements of human cognitive behavior could actually be modeled within Soar and which can only be extrapolated from it. The latter include concept learning, emotion, and motivation. A list of recommendations for the development of unified theories of cognition concludes the book.

This volume can be considered a how-to book. It defines steps that can be followed while trying to find a unique explanation of cognitive behavior and gives an example of how to use those steps. While this is the main value of the book, the theory it presents is interesting in its own right. The wide framework of the book, which discusses cognitive behavior from different points of view and shows how theoretical assumptions and concepts lead to a practical implementation, makes it a good survey of the current state of that part of AI that deals with problem solving and expert systems. Its completeness makes it a good introduction to the subject.

This book is up-to-date, well written, and interesting. It has no flaws, but I can still feel the loneliness of the long-distance runner within it. I recommend it highly.

Reviewer:  S. Zikkie Review #: CR114783
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