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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.
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. There are four principal themes to the collection: cooperative, non-sequential decisions; the representation and measurement of 'partially ordered' preferences; non-cooperative, sequential decisions; and pooling rules and Bayesian dynamics for sets of probabilities. The volume will be particularly valuable to philosophers concerned with decision theory, probability, and statistics, statisticians, mathematicians, and economists.
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".
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.
Issues for Feb. 1965-Aug. 1967 include Bulletin of the Institute of Management Sciences.