The Sciences of the Artificial

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MIT Press, Sep 26, 1996 - Computers - 248 pages
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Continuing his exploration of the organization of complexity and the science of design, this new edition of Herbert Simon's classic work on artificial intelligence adds a chapter that sorts out the current themes and tools -- chaos, adaptive systems, genetic algorithms -- for analyzing complexity and complex systems. There are updates throughout the book as well. These take into account important advances in cognitive psychology and the science of design while confirming and extending the book's basic thesis: that a physical symbol system has the necessary and sufficient means for intelligent action. The chapter "Economic Reality" has also been revised to reflect a change in emphasis in Simon's thinking about the respective roles of organizations and markets in economic systems.

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Herbert A. Simon (1978 Nobel Laureate in Economics) provides a classic treatise on complexity and the nature of objects and phenomena (aka, "artifacts"). In this text (ISBN 0-262-19374-4) he examines how human interactions with the natural world impact artifacts. Simon's legacy is perhaps captured by his work on complex systems. His thesis: "a physical symbol system has the necessary means for intelligent action" (cover). In other words, artifacts get their nature from their host systems which are "molded" by their environments (xi).
Simon's work links to design thinking. He considers how we may create artifacts "to attain goals" (abstract). He opens our minds to the fact that different disciplines concern themselves with the contingent--"not with how things are but with how they might be--in short, with design" (xii). He also tries to show us how natural science attempts to illustrate the simplicity of the physical world: "The central task of a natural science is to make the wonderful common-place: to show that complexity, correctly viewed, is only a mask for simplicity; to find pattern hidden in apparent chaos" (1). It is the pursuit and discernment of such patterns that help us to learn and to adapt--perhaps to evolve.
When we learn, we must remember that we really know less than we like to admit. We also don't always think rationally, particularly during decision making. We often rely upon shortcuts (rules of thumb, heuristics) to decide by "selective trial & error" (194) since we have limited time & memory (89). He observes that "human problem solving...involves nothing more than varying mixtures of trial and error and selectivity. The selectivity derives from various rules of thumb, or heuristics, that suggest which paths should be tried first and which leads are promising" (195). This talk of intuitive thinking sounds like Malcolm Gladwell, before Gladwell wrote.
Simon concludes that complex systems are hierarchic in nature. When designing alternative systems, we attempt to achieve desired end states by bridging the gap between present and desired circumstances. While the science of design is increasingly popular, more needs to be done to provide supporting substance in this emerging, multi-disciplinary field (113, 216).

Selected pages


Understanding the Natural and the Artificial Worlds
Economic Rationality Adaptive Artifice
The Psychology of Thinking Embedding Artifice in Nature
Remembering and Learning Memory as Environment for Thought
The Science of Design Creating the Artificial
Social Planning Designing the Evolving Artifact
Alternative Views of Complexity
The Architecture of Complexity Hierarchic Systems
Name Index
Subject Index

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