A theory of group decision-making applied to the Bay of Pigs and Cuban Missile Crisis decisions

This study of political decision-making stressing the process of decision-making in a group setting is, in part, a reaction against traditional approaches of political analysis. The study of international relations is overburdened with historical studies of the interaction between states. The classic approach to the study of a given decision by one government affecting another might be called the “rational actor model”. This model treats the state as the entity reaching the decision. The decision itself is seen as behavior that reflects a rational purpose or intent. The central concepts of the model center around the calculated weighing of goals, alternatives, consequences, and choices. The “rational actor model” is the dominant method of current political analysis. I will implicitly contend in this paper that the concept of foreign policy as a rational process of gathering information, setting alternatives, and making decisions is not an adequate tool of understanding. In fact, the “rational actor model” does not make sense out of much political phenomenon. I will directly contend in this paper that a process model of political decision-making provides an adequate and helpful tool for the understanding of political decisions

An Intentional Arithmetic for Qualitative Decision Making

Prescriptive decision analysis is a quantitative exercise. Options are assigned weights and probabilities to calculate an expected value. However, we view decision making as a qualitative process. Instead of converting qualitative features into numbers, we advocate converting numbers into qualitative features. As part of a larger effort to develop a decision simulation system [Slade et al. 1995], we are motivated to provide a principled means for automated, qualitative analysis. Following the artificial intelligence tradition of qualitative physics, we have developed an intentional arithmetic for interpreting quantitative data in a qualitative manner. Unlike the physical world, intentional domains require the analysis of the underlying goals of the decision maker. These goals, and their relative importance, provide a useful device for interpreting otherwise ambiguous data. In the next section, we discuss the background work in qualitative reasonsing and its relevance for decision making. We then describe our proposed intentional arithmetic for qualitative decision makin

Activity And Localization Of Maltodextrin Binding Site Mutants Of Glycogen Synthase In Saccharomyces Cerevisiae

Mentor: Wayne A. WilsonGlycogen is a glucose polymer formed by the enzyme glycogen synthase and is used in many organisms to store chemical energy. Saccharomyces cerevisiae (baker’s yeast) was used to study the activity and localization of glycogen synthase. Genes GSY1 and GSY2 encode glycogen synthase. GSY2 is responsible for the formation of Gsy2p, whose action accounts for ~90% of glycogen synthase activity; the remainder of total glycogen synthase activity stems from Gsy1p. Because glycogen synthase binds to glycogen, it can be used to determine glycogen localization. Glycogen synthase can appear in distinct patterns throughout the cell. Gsy2p has been shown to be regulated by phosphorylation. Phosphorylation of Gsy2p leads to inactivation of the enzyme, a decrease in glycogen storage, and a more localized pattern of glycogen synthase. Conversely, lowering the phosphorylation state of Gsy2p results in increased glycogen production and delocalization of glycogen synthase throughout the cell. Glucose-6-P (glucose-6-phosphate) activates glycogen synthase regardless of its phosphorylation state. We obtained a set of plasmids from a collaborator, encoding Gsy2p mutated at sites believed to be involved with maltodextrin binding. Maltodextrin is a chain of 20 or fewer dextrose molecules with α (1→4) glycosidic bonds. A protein sequence involved in maltodextrin binding likely would also bind to glycogen. Our task was to discover the localization pattern shown by the maltodextrin binding site mutants of glycogen synthase using a GFP tag on GSY2. The goal of this study was to determine the 16 effects of Gsy2p maltodextrin binding mutants on glycogen synthase activity, localization, and glycogen accumulation

The Generalization of a Decision Simulation

This paper discusses a research project in which an artificial intelligence decision making model in the domain of politics is applied to business decisions in general and an information technology decisions in particular. We describe the original VOTE program, which simulated Congressional roll call voting. Then we discuss extensions to VOTE motivated by its application to business domains. The primary sample decision problem is the purchase of a personal computer. The VOTE program is not a prescriptive model ofdecision making, but rather an attempt to create a realistic simulation of human cognitive behavior

Using Target Efficiency to Select Program Participants and Risk-Factor Models: An Application to Child Mental Health Interventions for Preventing Future Crime

Statistical risk factor models are often proposed for screening high-risk children to participate in early intervention programs. Recent contributions to the program evaluation literature demonstrate the need for incorporating judgments about relative importance of false positives versus false negatives in screening. This paper formalizes these judgments as commensurable economic costs and benefits and applies them to demonstrate an approach to participant selection motivated by the standard cost-benefit criterion of maximizing expected net benefits. Implications of this approach are explored using data from a mental health prevention trial. We illustrate the response of expected net benefits to the choice of a selection risk level, the sensitivity of the optimal selection risk level to per participant cost/benefit magnitudes, and the use of the target-efficiency approach for choosing among alternative risk-factor models. Several strategies that directly incorporate expected net benefit maximization as a criterion in the model estimation process are also examined.

QUALITATIVE DECISION EXPLANATION FOR INFORMATION TECHNOLOGY INVESTMENT

Many business decisions involve issues that are not amenable to quantitative measures and analysis. One such domain of decisions is large-scale investments in information technology. Traditional capital budgeting methods have not proven effective. In this paper, we present an alternative paradigm for qualitative decision analysis, embodied in the artificial intelligence program: VOTE. We describe the technology investment domain in general, and how VOTE models goals and agents in this domain. We apply the VOTE model to a specific decision taken from a. study of a major information technology investment decision.Information Systems Working Papers Serie

The training of professional linguists in the United Kingdom

SIGLEAvailable from British Library Document Supply Centre- DSC:DX92431 / BLDSC - British Library Document Supply CentreGBUnited Kingdo