Introduction, 99.-I. Some general features of rational choice, 100. II. The essential simplifications, 103.-III. Existence and uniqueness of solutions, 111.-IV. Further comments on dynamics, 113.-V. Conclusion, 114. Appendix, 115. Traditional economic theory postulates an "economic man," who, in the course of being "economic" is also "rational." This man is assumed to have knowledge of the relevant aspects of his environment which, if not absolutely complete, is at least impressively clear and voluminous. He is assumed also to have a well-organized and stable system of preferences, and a skill in computation that enables him to calculate, for the alternative courses of action that are available to him, which of these will permit him to reach the highest attainable point on his preference scale. Recent developments in economics, and particularly in the theory of the business firm, have raised great doubts as to whether this schematized model of economic man provides a suitable foundation on which to erect a theorywhether it be a theory of how firms do behave, or of how they "should" rationally behave. It is not the purpose of this paper to discuss these doubts, or to determine whether they are justified. Rather, I shall assume that the concept of "economic man" (and, I might add, of his brother "administrative man") is in need of fairly drastic revision, and shall put forth some suggestions as to the direction the revision might take. Broadly stated, the task is to replace the global rationality of economic man with a kind of rational behavior that is compatible with the access to information and the computational capacitiesthat are actually possessed by organisms, including man, in the kinds of environments in which such organisms exist. One is tempted to turn * The ideas embodied in this paper were initially developed in a series of discussions with Herbert Bohnert, Norman Dalkey, Gerald Thompson, and Robert Wolfson during the summer of 1952. These collaborators deserve a large share of the credit for whatever merit this approach to rational choice may possess. A first draft of this paper was prepared in my capacity as a consultant to the RAND Corporation. It has been developed further (including the Appendix) in work with the Cowles Commission for Research in Economics on "Decision Making Under Uncertainty," under contract with the Office of Naval Research, and has been completed with the aid of a grant from the Ford Foundation.

A growing interest in decision making in psychology is evidenced by the recent publication of Edwards' review article in the Psychological Bulletin (1) and the Santa Monica Conference volume, Decision Processes (7). In this work, much attention has been focused on the characterization of rational choice, and because the latter topic has been a central concern in economics, the theory of decision making has become a natural meeting ground for psychological and economic theory.A comparative examination of the models of adaptive behavior employed in psychology (e.g., learning theories), and of the models of rational behavior employed in economics, shows that in almost all respects the latter postulate a much greater complexity in the choice mechanisms, and a much larger capacity in the organism for obtaining information and performing computations, than do the former. Moreover, in the limited range of situations where the predictions of the two theories have been compared (see [7, Ch. 9, 10, 18]), the learning theories appear to account for the observed behavior rather better than do the theories of rational behavior.Both from these scanty data and from an examination of the postulates of the economic models it appears probable that, however adaptive the behavior of organisms in learning and choice situations, this adaptiveness falls far short of the ideal of "maximizing" postulated in economic theory. Evidently, organisms adapt well enough to "satisfice"; they do not, in general, "optimize."If this is the case, a great deal can be learned about rational decision making by taking into account, at the outset, the limitations upon the capacities and complexity of the organism, and by taking account of the fact that the environments to which it must adapt possess properties that permit further simplication of its choice mechanisms. It may be useful, therefore, to ask: How simple a set of choice mechanisms can we postulate and still obtain the gross features of observed adaptive choice behavior?In a previous paper (6) I have put forth some suggestions as to the kinds of "approximate" rationality that might be employed by an organism possessing limited information and limited computational facilities. The suggestions were "hypothetical" in that, lacking definitive knowledge of the human decisional processes, we can only conjecture on the basis of our everyday experiences, our introspection, and a very limited body of psychological literature what these Source: Psychological Review, 63(2) (1956): 129-138.

The central proposal of this article is that verbal reports are data. Accounting for verbal reports, as for other kinds of data, requires explication of the mechanisms by which the reports are generated, and the ways in which they are sensitive to experimental factors (instructions, tasks, etc.). Within the theoretical framework of human information processing, we discuss different types of processes underlying verbalization and present a model of how subjects, in response to an instruction to think aloud, verbalize information that they are attending to in short-term memory (STM). Verbalizing information is shown to affect cognitive processes only if the instructions require verbalization of information that would not otherwise be attended to. From an analysis of what would be in STM at the time of report, the model predicts what can reliably be reported. The inaccurate reports found by other research are shown to result from requesting information that was never directly heeded, thus forcing subjects to infer rather than remember their mental processes. After a long period of time during which stimulus-response relations were at the focus of attention, research in psychology is now seeking to understand in detail the mechanisms and internal structure of cognitive processes that produce these relations. In the limiting case, we would like to have process models so explicit that they could actually produce the predicted behavior from the information in the stimulus.

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We distinguish diagrammatic from sentential paper-and-pencil representations of information by developing alternative models of information-processing systems that are informationally equivalent and that can be characterized as sentential or diagrammatic. Sententiol representations are sequential, like the propositions in a text. Diagrammatic representations are indexed by location in a plane. Diagrammatic representations also typically display information that is only implicit in sentential representations and that therefore has to be computed, sometimer at great cost, to make it explicit for use. We then contrast the computational efficiency of these representations for solving several.illustrative problems in mathematics and physics.When two representations are informationally equivalent, their computational efficiency depends on the information-processing operators that act on them. Two sets of operators may differ in their capabilities for recognizing patterns, in the inferences they can carry out directly, and in their control strategies (in particular, the control of search). Diagrammatic and sentential representations sup part operators that differ in all of these respects. Operators working on one representation may recognize features readily or make inferences directly that are difficult to realize in the other representation. Most important, however, are differences in the efficiency of search for information and in the explicitness of information. In the representations we call diagrammatic, information is organized by location, and often much of the information needed to make an inference i s present and explicit at a single location. In addition, cues to the next logical step in the problem may be present at an adiacent location. Therefore problem solving can proceed through a smooth traversal of the diagram, and may require very little search or computation of elements that had been implicit.According to Bartfett's Quotations, "a picture is worth 10, OOO words" is a Chinese proverb. On inquiry, we find that the Chinese seem not to have heard of it, but the proverb is certainly widely known and widely believed in our culture. In particular, problem solvers in domains like physics and engineering make extensive use of diagrams, a form of pictures, in problem