Continuing his exploration of the organization of complexity and the science of design, this new edition of Herbert Simon's classic work on artificial ...

Complex systems are pervasive in the world around us. Making sense of a complex system should require that a person construct a network of concepts and principles about some domain that represents key (often dynamic) phenomena and their interrelationships. This raises the question of how expert understanding of complex systems differs from novice understanding. In this study we examined individuals' representations of an aquatic system from the perspective of structural (elements of a system), behavioral (mechanisms), and functional aspects of a (...) system. Structure–Behavior–Function (SBF) theory was used as a framework for analysis. The study included participants from middle school children to preservice teachers to aquarium experts. Individual interviews were conducted to elicit participants' mental models of aquaria. Their verbal responses and pictorial representations were analyzed using an SBF‐based coding scheme. The results indicated that representations ranged from focusing on structures with minimal understanding of behaviors and functions to representations that included behaviors and functions. Novices' representations focused on perceptually available, static components of the system, whereas experts integrated structural, functional, and behavioral elements. This study suggests that the SBF framework can be one useful formalism for understanding complex systems. (shrink)

The representation of physics problems in relation to the organization of physics knowledge is investigated in experts and novices. Four experiments examine the existence of problem categories as a basis for representation; differences in the categories used by experts and novices; differences in the knowledge associated with the categories; and features in the problems that contribute to problem categorization and representation. Results from sorting tasks and protocols reveal that experts and novices begin their problem representations with specifiably different problem categories, (...) and completion of the representations depends on the knowledge associated with the categories. For, the experts initially abstract physics principles to approach and solve a problem representation, whereas novices base their representation and approaches on the problem's literal features. (shrink)

A study is reported which focused on the problem-solving strategies employed by expert electronics engineers pursuing a real-world task: integrated-circuit design. Verbal protocol data were analysed so as to reveal aspects of the organisation and sequencing of ongoing design activity. These analyses indicated that the designers were implementing a highly systematic solution-development strategy which deviated only a small degree from a normatively optimal top-down and breadth-first method. Although some of the observed deviation could be described as opportunistic in nature, much (...) of it reflected the rapid depth-first exploration of tentative solution ideas. We argue that switches from a predominantly breadth-first mode of problem solving to depth-first or opportunistic modes may be an important aspect of the expert's strategic knowledge about how to conduct the design process effectively when faced with difficulties, uncertainties, and design impasses. (shrink)

Much of the cognitive lies beyond articulate, discursive thought, beyond the reach of current computational notions. In Sketches of Thought, Vinod Goel argues that the cognitive computational conception of the world requires our thought processes to be precise, rigid, discrete, and unambiguous; yet there are dense, ambiguous, and amorphous symbol systems, like sketching, painting, and poetry, found in the arts and much of everyday discourse that have an important, non-trivial place in cognition. Goel maintains that while on occasion our thoughts (...) do conform to the current computational theory of mind, they often are - indeed must be - vague, fluid, ambiguous, and amorphous. He argues that if cognitive science takes the classical computational story seriously, it must deny or ignore these processes, or at least relegate them to the realm of the nonmental. Along the way, Goel makes a number of significant and controversial interim points. He shows that there is a principled distinction between design and nondesign problems, that there are standard stages in the solution of design problems, that these stages correlate with the use of different types of external symbol systems, that these symbol systems are usefully individuated in Nelson Goodman's syntactic and semantic terms, and that different cognitive processes are facilitated by different types of symbol systems. (shrink)