Aggregation And Representation Of Preferences
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Author | : Andranick S. Tanguiane |
Publisher | : Springer Science & Business Media |
Total Pages | : 335 |
Release | : 2012-12-06 |
Genre | : Business & Economics |
ISBN | : 3642765165 |
Aggregation is the conjunction of information, aimed at its compact represen tation. Any time when the totality of data is described in terms of general ized indicators, conventional counts, typical representatives and characteristic dependences, one directly or indirectly deals with aggregation. It includes revealing the most significant characteristics and distinctive features, quanti tative and qualitative analysis. As a result, the information becomes adaptable for further processing and convenient for human perception. Aggregation is widely used in economics, statistics, management, planning, system analysis, and many other fields. That is why aggregation is so important in data pro cessing. Aggregation of preferences is a particular case of the general problem of ag gregation. It arises in multicriteria decision-making and collective choice, when a set of alternatives has to be ordered with respect to contradicting criteria, or various individual opinions. However, in spite of apparent similarity the problems of multicriteria decision-making and collective choice are somewhat different. Indeed, an improvement in some specifications at the cost of worsen ing others is not the same as the satisfaction of interests of some individuals to the prejudice of the rest. In the former case the reciprocal compensations are considered within a certain entirety; in the latter we infringe upon the rights of independent individuals. Moreover, in multicriteria decision-making one usu ally takes into account objective factors, whereas in collective choice one has to compare subjective opinions which cannot be measured properly.
Author | : Salvatore Greco |
Publisher | : Springer |
Total Pages | : 420 |
Release | : 2010-08-28 |
Genre | : Technology & Engineering |
ISBN | : 3642159761 |
Decision making is an omnipresent, most crucial activity of the human being, and also of virtually all artificial broadly perceived “intelligent” systems that try to mimic human behavior, reasoning and choice processes. It is quite obvious that such a relevance of decision making had triggered vast research effort on its very essence, and attempts to develop tools and techniques which would make it possible to somehow mimic human decision making related acts, even to automate decision making processes that had been so far reserved for the human beings. The roots of those attempts at a scientific analysis can be traced to the ancient times but – clearly – they have gained momentum in the recent 50 or 100 years following a general boom in science. Depending on the field of science, decision making can be viewed in different ways. The most general view can be that decision making boils down to some cognitive, mental process(es) that lead to the selection of an option or a course of action among several alternatives. Then, looking in a deeper way, from a psychological perspective this process proceeds in the context of a set of needs, preferences, rational choice of an individual, a group of individuals, or even an organization. From a cognitive perspective, the decision making process proceeds in the context of various interactions with the environment.
Author | : John Somerset Chipman |
Publisher | : |
Total Pages | : 102 |
Release | : 1979 |
Genre | : Consumption (Economics) |
ISBN | : |
Author | : John Charles Heaton |
Publisher | : |
Total Pages | : 198 |
Release | : 1989 |
Genre | : Consumers' preferences |
ISBN | : |
Author | : Davide Kantarcioglu |
Publisher | : Springer Nature |
Total Pages | : 133 |
Release | : 2022-06-01 |
Genre | : Computers |
ISBN | : 3031015681 |
Judgment aggregation is a mathematical theory of collective decision-making. It concerns the methods whereby individual opinions about logically interconnected issues of interest can, or cannot, be aggregated into one collective stance. Aggregation problems have traditionally been of interest for disciplines like economics and the political sciences, as well as philosophy, where judgment aggregation itself originates from, but have recently captured the attention of disciplines like computer science, artificial intelligence and multi-agent systems. Judgment aggregation has emerged in the last decade as a unifying paradigm for the formalization and understanding of aggregation problems. Still, no comprehensive presentation of the theory is available to date. This Synthesis Lecture aims at filling this gap presenting the key motivations, results, abstractions and techniques underpinning it. Table of Contents: Preface / Acknowledgments / Logic Meets Social Choice Theory / Basic Concepts / Impossibility / Coping with Impossibility / Manipulability / Aggregation Rules / Deliberation / Bibliography / Authors' Biographies / Index
Author | : Somdeb Lahiri |
Publisher | : |
Total Pages | : 16 |
Release | : 2017 |
Genre | : |
ISBN | : |
In this paper we present some results for preference aggregation functionals defined on rich admissible sets. Our results are concerned with an Independence of Irrelevant Alternatives assumption due to Alan D. Taylor suitably adjusted to be applicable in the framework of preference aggregation functionals. The initial step towards this adjustment is a version of Taylor's property due to Prasanta Pattanaik. We obtain several results which all point to its non-compatibility with a combination of other well-known assumptions that are often invoked in the literature concerning aggregation of preferences. A novel feature of our analysis is the mild requirement on the admissible set of utility profiles on which the preference aggregation functionals are defined for several of our results.
Author | : Douglas Blair |
Publisher | : |
Total Pages | : 25 |
Release | : 1980 |
Genre | : |
ISBN | : |
Author | : Masao Ogaki |
Publisher | : |
Total Pages | : 22 |
Release | : 1990 |
Genre | : |
ISBN | : |
Author | : Attila Ambrus |
Publisher | : |
Total Pages | : |
Release | : 2013 |
Genre | : |
ISBN | : |
Author | : Fuad T. Aleskerov |
Publisher | : Springer Science & Business Media |
Total Pages | : 260 |
Release | : 1999-03-31 |
Genre | : Business & Economics |
ISBN | : 9780792384519 |
Aggregation of individual opinions into a social decision is a problem widely observed in everyday life. For centuries people tried to invent the `best' aggregation rule. In 1951 young American scientist and future Nobel Prize winner Kenneth Arrow formulated the problem in an axiomatic way, i.e., he specified a set of axioms which every reasonable aggregation rule has to satisfy, and obtained that these axioms are inconsistent. This result, often called Arrow's Paradox or General Impossibility Theorem, had become a cornerstone of social choice theory. The main condition used by Arrow was his famous Independence of Irrelevant Alternatives. This very condition pre-defines the `local' treatment of the alternatives (or pairs of alternatives, or sets of alternatives, etc.) in aggregation procedures. Remaining within the framework of the axiomatic approach and based on the consideration of local rules, Arrovian Aggregation Models investigates three formulations of the aggregation problem according to the form in which the individual opinions about the alternatives are defined, as well as to the form of desired social decision. In other words, we study three aggregation models. What is common between them is that in all models some analogue of the Independence of Irrelevant Alternatives condition is used, which is why we call these models Arrovian aggregation models. Chapter 1 presents a general description of the problem of axiomatic synthesis of local rules, and introduces problem formulations for various versions of formalization of individual opinions and collective decision. Chapter 2 formalizes precisely the notion of `rationality' of individual opinions and social decision. Chapter 3 deals with the aggregation model for the case of individual opinions and social decisions formalized as binary relations. Chapter 4 deals with Functional Aggregation Rules which transform into a social choice function individual opinions defined as choice functions. Chapter 5 considers another model – Social Choice Correspondences when the individual opinions are formalized as binary relations, and the collective decision is looked for as a choice function. Several new classes of rules are introduced and analyzed.