Abstract This article describes a series of experiments which relate information to decision making. The experiments were developed with the objectives of validating a previously suggested conceptual model of information flow and its relation to decision making, as well as to establish specific values for the significant parameters involved. The conceptual approach related information to its effectiveness and therefore its use and value. Theory, measures, and relationships thus derived relate to the way information, once it is transmitted and received, is utilized by a decision maker. Specifically, information is said to be data of value in decision making. Starting with this definition it has been possible to define information quantitatively and to establish some of its properties and interrelationships. In the experiments described here a subject uses a computer terminal interactively in order to maximize subjective expected value over a number of courses of action available to him by choosing what be believes to be an optimal course of action at each trial. A decision‐making situation is formulated in terms of value and probability matrices, unknown to the subject. The subject is instructed to maximize the sum of the outcome values obtained, and through feedback to learn the structure and the probabilities involved. Data were obtained from 60 subjects each experimenting on 12 different matrices. These data generally validated the theoretical approach and also enabled the determination of specific values for significant parameters involved. The experimental design is described in detail in the article. Analysis of some of the data is presented.

Abstract This series of articles describes research which has been underway at The Ohio State University in an effort to develop a fundamental and general theory of information flow and analysis. More specifically, the research attempts to (1) identify and quantify important variables and parameters in the information flow process; (2) establish relationships among these variables; (3) apply the theory to practical situations and to examine the resulting implications; and (4) develop models, both simulation and experimental, to utilize and validate the theory. The basis for our work treats information as data of value in decision‐making. This, in turn, leads to a powerful model of a Generalized Information System. We have now made considerable progress and have developed the basic elements comprising a generalized theory. In particular, we have been able to establish quantitative definitions for and relationships among: quantity of information, value of information, effectiveness of information, decision‐maker effectiveness, decision‐maker performance, and other terms. By dealing with “average” decision‐makers, we establish unique relationships for specific decision situations. Typical relationships and curves are presented in the articles. We describe a flexible, sophisticated simulation model which permits the examination of the interrelationship between information and decision‐making for a wide variety of different situations. We present detailed simulation results for two specific examples‐a typical farmer and a mathematical example. We describe prototype experiments which place human decision‐makers in an interactive decision‐making situation. We are able to obtain data on their decision‐making behavior in the light of our conceptual model. Preliminary analysis of the data is described.

Abstract This series of articles describes research which has been underway at The Ohio State University in an effort to develop a fundamental and general theory of information flow and analysis. More specifically, the research attempts to (1) identify and quantify important variables and parameters in the information flow process; (2) establish relationships among these variables; (3) apply the theory to practical situations and to examine the resulting implications; and (4) develop models, both simulation and experimental, to utilize and validate the theory. The basis for our work treats information as data of value in decision‐making. This, in turn, leads to a powerful model of a Generalized Information System. We have now made considerable progress and have developed the basic elements comprising a generalized theory. In particular, we have been able to establish quantitative definitions for and relationships among quantity of information, value of information, effectiveness of information, decision‐maker effectiveness, decision‐maker performance, and other terms. By dealing with “average” decision‐makers, we establish unique relationships for specific decision situations. Typical relationships and curves are presented in the articles. We describe a flexible, sophisticated simulation model which permits the examination of the interrelationship between information and decision‐making for a wide variety of different situations. We present detailed simulation results for two specific examples‐a typical farmer and a mathematical example. We describe prototype experiments which place human decision‐makers in an interactive decision‐making situation. We are able to obtain data on their decision‐making behavior in the light of our conceptual model. Preliminary analysis of the data is described.

Abstract This series of articles describes research which has been underway at The Ohio State University in an effort to develop a fundamental and general theory of information flow and analysis. More specifically, the research attempts to (1) identify and quantify important variables and parameters in the information flow process; (2) establish relationships among these variables; (3) apply the theory to practical situations and to examine the resulting implications; and (4) develop models, both simulation and experimental, to utilize and validate the theory. The basis for our work treats information as data of value in decision‐making. This, in turn, leads to a powerful model of a Generalized Information System. We have now made considerable progress and have developed the basic elements comprising a generalized theory. In particular, we have been able to establish quantitative definitions for and relationships among quantity of information, value of information, effectiveness of information, decision‐maker effectiveness, decision‐maker performance, and other terms. By dealing with “average” decision‐makers, we establish unique relationships for specific decision situations. Typical relationships and curves are presented in the articles. We describe a flexible, sophisticated simulation model which permits the examination of the interrelationship between information and decision‐making for a wide variety of different situations. We present detailed simulation results for two specific examples—a typical farmer and a mathematical example. We describe prototype experiments which place human decision‐makers in an interactive decision‐making situation. We are able to obtain data on their decision‐making behavior in the light of our conceptual model. Preliminary analysis of the data is described.

article Free Access Share on Compilation of Acyclic Smooth Programs for Parallel Execution Authors: Otto C. Juelich Missile Systems Division, Rockwell International, Columbus, OH Missile Systems Division, Rockwell International, Columbus, OHView Profile , Clinton R. Foulk Department of Computer and Information Science, The Ohio State University, 2036 Neil Avenue Mall, Columbus, OH Department of Computer and Information Science, The Ohio State University, 2036 Neil Avenue Mall, Columbus, OHView Profile Authors Info & Claims ACM Transactions on Programming Languages and SystemsVolume 3Issue 1Jan. 1981 pp 24–48https://doi.org/10.1145/357121.357124Published:01 January 1981Publication History 1citation201DownloadsMetricsTotal Citations1Total Downloads201Last 12 Months5Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my Alerts New Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF