The type of cognitive system (CS) studied here has four basic parts: (1) a set of interacting elementary productions, called classifiers , (2) a performance algorithm that directs the action of the system in the environment, (3) a simple learning algorithm that keeps a record of each classifier's success in bringing about rewards, and (4) a more complex learning algorithm, called the genetic algorithm , that modifies the set of classifiers so that variants of good classifiers persist and new, potentially better ones are created in a provably efficient manner.

Like experts in other fields, expert computer programmers can recall at a glance far more information relevant to their field than novices can. One explanation for this difference is that experts not only have more information, they have it better organized into meaningful chunks. In this paper, we infer the details of individual programmers' chunks of key programming concepts using the Reitman-Rtreter (Cognitive Psychology, 1980, 12(4), 5.54-581.) technique for inferring tree structures from recall orders. Differences in organizations accompany skill-level differences. Beginner programmers' organizations show a rich variety of commonlanguage associations to these programming concepts; Intermediate programmers show mixtures of programming and common-language associations; and Experts show remarkably similar, but not identical, organizations based clearly on programming knowledge. Experts and novices differ in their abilities to process large amounts of meaningful information. This difference has been seen in the domains of chess, Go, electronics, bridge, music, and physics (

This paper concerns the problem of abstraction: whether when we encounter several exemplars of a concept, we retain only the abstracted concept, only the exemplars, or both. Although many studies concur that both are stored, a recent article argued strongly that only the abstracted concept is stored. The present study, aimed at replication of this recent finding, follows the earlier procedural details but adds appropriate controls and uses simpler material. A set of 24 exemplars of four concepts, in the form of four-tuples of letters and numbers, was presented to Ss who, after presentation, rated a larger set of exemplars for recognition. One group of Ss experienced the conceptual exemplars; control group Ss experienced items that were similar in composition but not exemplars of a concept. Two major results appeared: Unlike the study on which this was based, all Ss were able to distinguish those items that were originally experienced from those that were not. And, the more completely an exemplar fit the concept (the longer the item), the more confident the S was that it had been presented. In contrast, in the control condition, the longer the item, the more confident the S was that it had not been presented earlier. Two models are described to account for these results. One is based on the S's initial storage of the exemplars in a concept-plus-correction format; the other is based on a procedure whereby the S can make recognition judgments without having previously abstracted and retained the concepts. This paper concerns the age-old problem of abstraction. There are two fundamental questions that learning theorists have asked regarding abstraction: (1) what are the processes by which general principles are

The technique introduced here induces the organization of information in memory from systematic inspection of regularities in free recall. The form of the representation of this organization is an "ordered tree." The technique has the advantage of being based on a theory of the way in which the data were generated and can be shown to produce a unique structure that captures all the kinds of regularities the theory of recall prescribes. Also presented is a collateral technique for measuring the amount of organization evidenced in a struture, as well as a procedure for identifying errors. The experimental work shows the technique's ability to recover the details of an organization presented to subjects and provides converging evidence for the particular structures induced from the pattern of recall pauses. In addition, the application of the technique to structures unknown a priori produced organizations that were easy to interpret and a second set of pauses that further confirmed the details of the induced structures.

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