Organization and Decision Theory


Book Description

Ira Horowitz Depending upon one's perspective, the need to choose among alternatives can be an unwelcome but unavoidable responsibility, an exciting and challenging opportunity, a run-of-the-mill activity that one performs seem ingly "without thinking very much about it," or perhaps something in between. Your most recent selections from a restaurant menu, from a set of jobs or job candidates, or from a rent-or-buy or sell-or-Iease option, are cases in point. Oftentimes we are involved in group decision processes, such as the choice of a president, wherein one group member's unwelcome responsibility is another's exciting opportunity. Many of us that voted in the presidential elections of both 1956 and 1984, irrespective of political affiliation, experienced both emotions; others just pulled the lever or punched the card without thinking very much about it. Arriving at either an individual or a group decision can sometimes be a time consuming, torturous, and traumatic process that results in a long regretted choice that could have been reached right off the bat. On other occasions, the "just let's get it over with and get out of here" solution to a long-festering problem can yield rewards that are reaped for many 1 ORGANIZATION AND DECISION THEORY 2 years to come. One way or another, however, individuals and organiza tions somehow manage to get the decision-making job done, even if they don't quite understand, and often question, just how this was accomplished.




Rethinking the Foundations of Statistics


Book Description

This important collection of essays is a synthesis of foundational studies in Bayesian decision theory and statistics. An overarching topic of the collection is understanding how the norms for Bayesian decision making should apply in settings with more than one rational decision maker and then tracing out some of the consequences of this turn for Bayesian statistics. The volume will be particularly valuable to philosophers concerned with decision theory, probability, and statistics, statisticians, mathematicians, and economists.




Evaluation and Decision Models with Multiple Criteria


Book Description

Formal decision and evaluation models are so widespread that almost no one can pretend not to have used or suffered the consequences of one of them. This book is a guide aimed at helping the analyst to choose a model and use it consistently. A sound analysis of techniques is proposed and the presentation can be extended to most decision and evaluation models as a "decision aiding methodology".




Advances in Decision Research


Book Description

These papers stem from a biennial conference which constitutes an international and interdisciplinary forum for scientists dealing with modeling, analyzing and aiding decision processes. The contributions in the first part offer criticisms and challenges for the study of human decision making and the design of valid decision-support methods, programs or systems. The second part presents formal models and empirical analyses of human decision behavior in group situations, connecting perspectives and paradigms from decision theory, game theory and social psychology. The third section examines the practical limits and strengths in the application of decision analysis. The following section is devoted to prescription: How shall we design computer systems to help decision makers? The last group of papers are instructive examples of problem oriented research, exploring the utility of decision research for the analysis of "real" decision processes.




Uncertainty in Artificial Intelligence 5


Book Description

This volume, like its predecessors, reflects the cutting edge of research on the automation of reasoning under uncertainty.A more pragmatic emphasis is evident, for although some papers address fundamental issues, the majority address practical issues. Topics include the relations between alternative formalisms (including possibilistic reasoning), Dempster-Shafer belief functions, non-monotonic reasoning, Bayesian and decision theoretic schemes, and new inference techniques for belief nets. New techniques are applied to important problems in medicine, vision, robotics, and natural language understanding.