Ecological rationality

About: Ecological rationality is a research topic. Over the lifetime, 2326 publications have been published within this topic receiving 102678 citations.

A Behavioral Model of Rational Choice

Abstract: : A model is proposed for the description of rational choice by organisms of limited computational ability.

Rational choice and the structure of the environment.

Abstract: 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

Reasoning the fast and frugal way: models of bounded rationality.

Abstract: Humans and animals make inferences about the world under limited time and knowledge. In contrast, many models of rational inference treat the mind as a Laplacean Demon, equipped with unlimited time, knowledge, and computational might. Following H. Simon's notion of satisficing, the authors have proposed a family of algorithms based on a simple psychological mechanism: onereason decision making. These fast and frugal algorithms violate fundamental tenets of classical rationality: They neither look up nor integrate all information. By computer simulation, the authors held a competition between the satisficing "Take The Best" algorithm and various "rational" inference procedures (e.g., multiple regression). The Take The Best algorithm matched or outperformed all competitors in inferential speed and accuracy. This result is an existence proof that cognitive mechanisms capable of successful performance in the real world do not need to satisfy the classical norms of rational inference.

Heuristic Decision Making

Abstract: As reflected in the amount of controversy, few areas in psychology have undergone such dramatic conceptual changes in the past decade as the emerging science of heuristics. Heuristics are efficient cognitive processes, conscious or unconscious, that ignore part of the information. Because using heuristics saves effort, the classical view has been that heuristic decisions imply greater errors than do “rational” decisions as defined by logic or statistical models. However, for many decisions, the assumptions of rational models are not met, and it is an empirical rather than an a priori issue how well cognitive heuristics function in an uncertain world. To answer both the descriptive question (“Which heuristics do people use in which situations?”) and the prescriptive question (“When should people rely on a given heuristic rather than a complex strategy to make better judgments?”), formal models are indispensable. We review research that tests formal models of heuristic inference, including in business organizations, health care, and legal institutions. This research indicates that (a) individuals and organizations often rely on simple heuristics in an adaptive way, and (b) ignoring part of the information can lead to more accurate judgments than weighting and adding all information, for instance for low predictability and small samples. The big future challenge is to develop a systematic theory of the building blocks of heuristics as well as the core capacities and environmental structures these exploit.

Intention, Plans, and Practical Reason

Abstract: 1. Introduction 2. On the way to the planning theory 3. Plans and practical reasoning 4. Agent rationality: toward a general theory 5. Reconsideration and rationality 6. Agent rationality: the historical theory 7. Commitment revisited 8. Two faces of intention 9. Acting with an intention 10. Intention and expected side effects 11. Conclusion Bibliography Notes Index.