Utility Theory

The axiomatic framework of quantum game theory gives us a new platform for exploring economics by resolving the foundational problems that have long plagued the expected utility hypothesis. This platform gives us a previously unrecognized tool in economics, the statistical ensemble, which we apply across three distinct economic spheres. We examine choice under uncertainty and find that the Allais paradox disappears. For over seventy years, this paradox has acted as a barrier to investigating human choice by masking actual choice heuristics. We discover a powerful connection between the canonical ensemble and neoclassical economics and demonstrate this connection's predictive capability by examining income distributions in the United States over 24 years. This model is an astonishingly accurate predictor of economic behavior, using just the income distribution and the total exergy input into the economy. Finally, we examine the ideas of equality of outcome versus equality of opportunity. We show how to formally consider equality of outcome as a Bose-Einstein condensate and how its achievement leads to a corresponding collapse in economic activity. We call this new platform 'statistical economics' due to its reliance on statistical ensembles.

The first axiom of the Analytic Hierarchy Process (AHP) states that the pairwise comparison judgments are reciprocal. Here we explore the relationships between the reciprocal property and preference relations with and without the axiom of transitivity and point out some important distinctions between utility theory and the AHP.

We formulate a new theory of expected utility in which risk and uncertainty is modelled by the usage of a so called event space which is a natural generalisation of a state space. The basic idea is that the decision maker for each group of related decisions creates a "small world" (a local state space) from the events in the "grand world" (the event space). We introduce a set of preference axioms similar in spirit to the Savage axioms, and show that they lead to a a more general expected utility theory, where in each "small world" risk is described by an additive probability measure. All local risk measures appear as restrictions of a common integrated additive expectation functional defined on the "grand world". A benefit of the theory is that it allows for an intuitive distinction between risk and uncertainty. In particular, there is a numerical measure of the degree of uncertainty aversion associated with a given preference relation, which can be calculated. We illustrate the use of the theory for the Ellsberg paradox and for a no-trade portfolio decision problem, none of which can be captured using standard expected utility theory. JEL classification: D8 and G12.

We formulate a new theory of expected utility in which risk and uncertainty is modelled by the usage of a so called event space which is a natural generalisation of a state space. The basic idea is that the decision maker for each group of related decisions creates a "small world" (a local state space) from the events in the "grand world" (the event space). We introduce a set of preference axioms similar in spirit to the Savage axioms, and show that they lead to a a more general expected utility theory, where in each "small world" risk is described by an additive probability measure. All local risk measures appear as restrictions of a common integrated additive expectation functional defined on the "grand world". A benefit of the theory is that it allows for an intuitive distinction between risk and uncertainty. In particular, there is a numerical measure of the degree of uncertainty aversion associated with a given preference relation, which ...

Several approaches have been proposed for evaluating information in expected utility theory. Among the most popular approaches are the expected utility increase, the selling price and the buying price. While the expected utility increase and the selling price always agree in ranking information alternatives, Hazen and Sounderpandian have demonstrated that the buying price may not always agree with the other two. That is, in some cases, where the expected utility increase would value information A more highly than information B, the buying price may reverse these preferences. In this paper, we discuss the conditions under which all these approaches agree in a generic decision environment where the decision maker may choose to acquire arbitrary information bundles.

Pilotaj eğitimi, başlangıç ve ileri seviye eğitim uçaklarının kullanıldığı filolarda teorik ve pratik fazlardan oluşan uzun bir süreçtir. Aday pilot, bu safhaları geçtikten sonra tekâmül safhasına geçmektedir. Pilot adayının yeteneklerinin belirlenmesi açısından, eğitim uçağının donanımı son derece önemlidir. Eğitim uçağının donanımındaki limitler, pilot adayının yeteneklerini göstermesi açısından engel teşkil etmemelidir. Bu nedenle eğitim uçağı seçimi kritik bir karar sürecidir ve bu süreçte çok sayıda nicel ve nitel kriter göz önünde bulundurulmalıdır. Bu çalışmada, literatür taraması ve uzmanlardan alınan görüşler doğrultusunda; altı kriter ve yirmi yedi alt kriter değerlendirme aşamasında kullanılmak üzere belirlenmiştir. Bu kriterler, belirlenen yedi alternatif eğitim uçağının seçiminde dikkate alınmıştır. Bu çalışmada kriterlerin ağırlıklarının belirlenmesi için Analitik Hiyerarşi Süreci (AHP), alternatif uçakların sıralaması için TOPSIS yöntemi kullanılmıştır. İlave olarak eğitim uçağı seçiminde etkili bir karar verme için Hedef Programlama modeli önerilmiş, AHP ile bulunan kriter ağırlıkları, TOPSIS yöntemiyle bulunan alternatiflerin sıralama değerleri matematiksel modele girdi olarak dahil edilmiştir. Ayrıca matematiksel modele farklı kısıtlar (Bütçe, yerli kaynaklarla üretilmiş olma vb.) eklenmiştir. Bu kısıtların yanı sıra kurulan farklı senaryolar da değerlendirmiş ve karar vericilere optimal alternatiflerin belirlenmesinde rehberlik hedeflenmiştir. Sonuç olarak, bu çalışmada eğitim uçağı seçimi sürecinde kullanılabilecek etkili bir karar verme modeli sunulmaktadır. Entegre edilen yöntemler ve dikkate alınan kısıtlar, karar vericilere objektif ve bilgiye dayalı bir karar alma süreci sunmaktadır. Bu çalışmanın literatüre katkısı, eğitim uçağı seçiminde farklı karar verme yöntemlerinin entegre şekilde uygulanması, farklı kriterlerin ve kısıtların değerlendirilmesi ve yerli kaynaklarla üretilmiş olma kriterinin ilk kez dikkate alınmış olmasıdır.

This article examines the relationship between risk, return, skewness, and utility-based preferences. Examples are constructed showing that, for any commonly used utility function, it is possible to have two continuous unimodal random variables X and Y with positive and equal means, X having a larger variance and lower positive skewness than Y , and yet X has larger expected utility than Y , contrary to persistent folklore concerning U > 0 implying skewness preference for risk averters. In additon, it is shown that ceteris paribus analysis of preferences and moments, as occasionally used in the literature, is impossible since equality of higher-order central moments implies the total equality of the distributions involved.

Nicholas Georgescu-Roegen is one of the most famous Romanian economists. From the point of view of the schools of economic thought, his writings are not part of the orthodox typology. An original and unconventional spirit, Nicholas Georgescu-Roegen is at the same time an important representative of the mathematics economics and "a profoundly humane and wise philosopher" as Paul Samuelson described him. His work is so atypical especially given the way he analyses economic phenomena and processes seen in connection with the processes taking place in the immediate environment. The economic and philosophic concept of entropy, based upon the second law of thermodynamics, is indissolubly linked to Georgescu-Roegen's name, him thus becoming a paradigm creator. In his turn, the term of bio-economics rests upon Georgescu-Roegen's idea that there is an analogy between the biological and the economical worlds.

Simulation is so important and crucial
because it finally provides the social sciences with a truly “experimental” method for the validation and
adjustment of the models and, in particular, for the specification of working architectures and not mere formal
descriptions. Such experimental support is even more crucial for the
development of new social policies and strategies than for social theory per se. we stress the role of Agent-based social simulation (ABSS). It provides the social sciences
with "a generative approach"

This paper aims to represent the special characteristics of rational economics in comparison to the case of the behavioral economics. Therefore, in this analysis are represented these issues, and showed the main differences between the two concepts. Therefore, the mainstream is to show the crucial attributes for both of them, and differences between them.

Under the prevailing financial constraints and rapid infrastructure deterioration, funding decisions for renewal (rehabilitation) projects have become large challenges for engineers and economists alike. However, existing prioritization and ranking methods suffer from serious drawbacks of not considering multi-year and multi funding scenarios. Moreover, optimization efforts in the literature employ sophisticated mechanisms without providing a structured strategy or justification behind the funding solution. To overcome these drawbacks and to arrive at optimum and economically justifiable infrastructure funding decisions, this research provides a decision support system by adopting well-established concepts from the science of Microeconomics that relate to Consumer Theory and Behavioural Economics. The new decision support system has been developed with two components: (1) an enhanced benefit-cost analysis (EBCA) heuristic approach that arrives at optimum decisions by targeting equilibrium among the different renewal expenditure categories, using the equal marginal utility per dollar concept; and (2) a visual what-if analysis inspired by the indifference maps concept to study the sensitivity of decisions under different budget levels. The developed decision support system has been validated through a number of case studies including a case study were different categories of assets (pavements, bridges) are co-located. The results proved the capability of the system to arrive at optimum funding decisions supported with economic justification. Using the behavioural economic concept of "Loss-aversion", this research also compared the strategy of minimizing loss against the typical strategy of maximizing gain in the infrastructure funding decisions. In essence, this research is aiming at improving this crucial infrastructure funding problem by integrating the two worlds of microeconomics and asset management. Such integration will help provide optimum funding decisions, increase the credibility of funding methods to the public, and justify the spending of tax payer's money on infrastructure rehabilitation projects.

A navegação consulta e descarregamento dos títulos inseridos nas Bibliotecas Digitais UC Digitalis, UC Pombalina e UC Impactum, pressupõem a aceitação plena e sem reservas dos Termos e Condições de Uso destas Bibliotecas Digitais, disponíveis em https://digitalis.uc.pt/pt-pt/termos. Conforme exposto nos referidos Termos e Condições de Uso, o descarregamento de títulos de acesso restrito requer uma licença válida de autorização devendo o utilizador aceder ao(s) documento(s) a partir de um endereço de IP da instituição detentora da supramencionada licença. Ao utilizador é apenas permitido o descarregamento para uso pessoal, pelo que o emprego do(s) título(s) descarregado(s) para outro fim, designadamente comercial, carece de autorização do respetivo autor ou editor da obra. Na medida em que todas as obras da UC Digitalis se encontram protegidas pelo Código do Direito de Autor e Direitos Conexos e demais legislação aplicável, toda a cópia, parcial ou total, deste documento, nos casos em que é legalmente admitida, deverá conter ou fazer-se acompanhar por este aviso. The use of the multiattribute utility theory to measure the stability of patients' quality judgments

It is shown that an arbitrary game with effective small groups is approximately a market game. Small groups are effective if all or almost all gains to collective activities can be achieved by groups bounded in absolute size. Market games are games derived from markets where all agents have continuous, concave payoff functions. Bounds on the closeness of the approximation are stated in terms of the extent of substitution-the closeness of substitutes for each player-and other parameters characterizing the games. In this respect our results resemble those of Starr (1969) and Anderson (1978), for example, on approximate equilibrium and cores in exchange economies. In contrast with the market-game equivalence results of Shubik and Wooders (1982) and Wooders (1993,1994) no topology on the space of player types is required-the results are for arbitrary games.

Utilitarianism is an ethical theory that suggests actions should be evaluated based on their outcomes, specifically in maximising overall happiness or well-being. In Appropriate /Alternative Dispute Resolution (ADR), a utilitarian framework will help select processes and solutions that enhance collective welfare while minimising negative impacts on individuals.

Homo Economicus or economic man, which is the main postulate of classical and neo-classical theories indicate a rational person who makes decisions and pursues wealth for his self-interest. But, human-being is not a rational agent all the time. Because most of the time, some other factors determine human behavior than rationality. These could be repetition, imitation, or social norms. Therefore; behavioral economics, having introduced a distinctive perspective to economics, argues that people cannot make rational decisions and can be rational only to a limited extent in their decision. This study aims to present a historical perspective in molding the Homo Economicus in the Economics Discipline.

This paper presents a methodology to determine the preferences of an individual facing risk in the framework of (non)-expected utility theory. When individual preference satisfies a given invariance property, his utility function is solution of a functional equation associated to a specific transformation. Conversely, there exist transformations characterizing any given utility function and its invariance property. More precisely, invariance with respect to two transformations uniquely determines the individual utility function. We provide examples of such transformations for CARA or CRRA utility, but also with any other utility specification and discuss the example of DARA and IRRA specifications. JEL classification: C90, D81.

In the paper, we consider the application of the theory of probability metrics in several areas in the field of finance. First, we argue that specially structured probability metrics can be used to quantify stochastic dominance relations. Second, the methods of the theory of probability metrics can be used to arrive at a general axiomatic treatment of dispersion measures and probability metrics can be used to describe continuity of risk measures. Finally, the methods of probability metrics theory are applied to the benchmark-tracking problem significantly extending the problem setting.

Using results from neurobiology on perceptual decision making and value-based decision making, the problem of decision making between lotteries is reformulated in an abstract space where uncertain prospects are mapped to corresponding active neuronal representations. This mapping allows us to maximize non-extensive entropy in the new space with some constraints instead of a utility function. To achieve good agreements with behavioral data, the constraints must include at least constraints on the weighted average of the stimulus and on its variance. Both constraints are supported by the adaptability of neuronal responses to an external stimulus. By analogy with thermodynamic and information engines, we discuss the dynamics of choice between two lotteries as they are being processed simultaneously in the brain by rate equations that describe the transfer of attention between lotteries and within the various prospects of each lottery. This model is able to give new insights on risk ave...

This paper reconstructs the history of experimental research on consumer demand behavior between 1930 and 1970. The backgrounds of the experiments and their impact on the development of consumption theory are also investigated. Among other things, the paper shows that in fact many prominent economists of the period were involved in this stream of research.

The relationship between MAUT and AHP for three-level hierarchic structures is demonstrated based on a common framework interpreting multiattribute decision making techniques. A theorem showing the conditions under which two multiattribute decision making techniques result in a consistent preference structure is proved. It can be justified based on this theorem that the rank reversal problem in AHP resulting from the addition or deletion of alternatives is caused by multiplying inappropriate criteria priorities with local priorities for alternatives. A scaling method, AHW, is introduced synthesizing judgments from pairwise comparisons within and among criteria into value scales in MAUT.

Pilot training is a long process that consists of theoretical and practical phases in fleets that
use both basic and advanced training aircraft. After passing these phases, a prospective pilot
progresses to the advanced stage. The equipment of the training aircraft is extremely
important in determining the capabilities of the trainee pilot. The limitations of the training
aircraft's equipment should not hinder the demonstration of the trainee pilot's abilities.
Therefore, the selection of training aircraft is a critical decision-making process, requiring
consideration of numerous quantitative and qualitative criteria. In this study, six main criteria
and twenty-seven sub-criteria have been identified for the evaluation stage based on a
literature review and expert opinions. These criteria have been considered in the selection of
seven alternative training aircraft. The Analytic Hierarchy Process (AHP) was used to
determine the weights of the criteria in this study, while the TOPSIS method was employed
to rank the alternative aircraft. Additionally, a Goal Programming model was proposed to
facilitate effective decision-making in the selection of training aircraft. The weights of the
criteria found through AHP and the ranking values of the alternatives obtained via the
TOPSIS method were included as inputs in the mathematical model. Various constraints
(e.g., budget, domestic production) were also incorporated into the mathematical model.
Different scenarios were evaluated alongside these constraints to guide decision-makers in
identifying the optimal alternatives. In conclusion, this study presents an effective decisionmaking model that can be utilized in the process of selecting training aircraft. The integrated
methods and considered constraints provide decision-makers with an objective and informed
decision-making process. The contribution of this study to the literature lies in the integrated
application of different decision-making methods in the selection of training aircraft, the
evaluation of various criteria and constraints, and the consideration of domestic production
criteria for the first time.

The contents of this report reflect the views of the authors who are responsible for the facts and the accuracy of the data presented herein. The contents do not necessarily reflect the official views of the Federal Highway Administration and the Indiana Department of Transportation. This report does not constitute a standard, a specification, or a regulation.

The contents of this report reflect the views of the authors who are responsible for the facts and the accuracy of the data presented herein. The contents do not necessarily reflect the official views of the Federal Highway Administration and the Indiana Department of Transportation. This report does not constitute a standard, a specification, or a regulation.

Recent developments in generalized probability theory have renewed a debate about whether regularity (i.e., the constraint that only logical contradictions get assigned probability 0) should be a necessary feature of both chances and credences. Crucial to this debate, however, are some mathematical facts regarding the interplay between the existence of regular generalized probability measures and various cardinality assumptions. We improve on several known results in the literature regarding the existence of regular generalized probability measures. In particular, we give necessary and sufficient conditions for the existence of regular generalized probability measures defined on the whole powerset of any sample space. arguing about the plausibility, or lack thereof, of any such principles but only with the mathematical relations between regularity and totality.

A systematic multicriteria decision analysis technique is described for contractor selection and bid evaluation based on utility theory and which permits different types of contractor capabilities to be evaluated. A UK case study is used to illustrate the technique. The theoretical basis and the advantages of the technique are also presented.

Negotiations in which participants exchange offers based on their chosen positions can be extended to include dialogue about their interests. Revelation of negotiators' interests allows them to make more acceptable offers and perhaps propose possible alternative approaches toward each other's interests, both of which may result in mutually and individually beneficial outcomes. However, it can also expose their strategies, and possibly their dependencies on other negotiators toward the achievement of their goals. Revealing this information can leave them vulnerable to extortion or retribution, but it can also be used to gain sympathy or build a relationship of trust and reciprocity.

Multiple criteria decision-making methods enable to choose the optimal decision, if his criterions is contradictorys. In herein paper is describe MAUT – multiattribute utility theory. This method is reasoned in theory. MAUT up for indeterminations situations, but can to use for determinations situations. In this method multiple criteria problem solvable with the help of unitary utility functions.

We introduce a framework which is based on probabilistic Description logics (Prob-DL), to represent and solve multi-criteria discrete alternative problems by calculating expected utility. To our knowledge, this is the first ever approach for calculating expected utility using a description logics based formalism.

Static multi-criteria problem of investing in innovative projects on a set of coalitional partitions finding means compromise vector (one or more) of investment programs, where each component is an investment program of the corresponding innovative project. The search of compromise vector is made under coalitional interaction of all participants in innovative projects. In the process of solving this problem several game problems with different coalitional partitions are considered. As the principles of optimality, Pareto optimum, Nash arbitration scheme, Shapley value, compromise solution are used.

Static multi-criteria problem of investing in innovative projects on a set of coalitional partitions finding means compromise vector (one or more) of investment programs, where each component is an investment program of the corresponding innovative project. The search of compromise vector is made under coalitional interaction of all participants in innovative projects. In the process of solving this problem several game problems with different coalitional partitions are considered. As the principles of optimality, Pareto optimum, Nash arbitration scheme, Shapley value, compromise solution are used.

This short paper shows that the Allais Paradox and the Common Ratio Effect-regarded as classic examples of the violation of the Expected Utility Theory Axioms-may be easily explained by assuming that changes in wealth (i.e. gains and losses) are perceived in relative terms. The

Surprise is a widely used concept describing a range of phenomena from unexpected events to behavioral responses. We propose a measure of surprise, to arrive at a new framework for surprise-driven learning. There are two components to this framework: (i) a confidence-adjusted surprise measure to capture environmental statistics as well as subjective beliefs, (ii) a surprise-minimization learning rule, or SMiLe-rule, which dynamically adjusts the balance between new and old information without making prior assumptions about the temporal statistics of the environment. We apply our framework to a dynamic decision-making task and a maze exploration task to demonstrate that it is suitable for learning in complex environments, even if the environment undergoes gradual or sudden changes. Our proposed surprise-modulated belief update algorithm provides a framework to study the behavior of humans and animals encountering surprising events.

This issue marks the 50th volume, and year, of the publication of the Journal of Supply Chain Management. As such, this is an opportune moment to look back at the last 50 years and the more recent 2008-13 time period since the Journal's repositioning. It is also an opportunity to prospectively consider our steps as we move ahead as a scholarly journal and as a discipline. In doing so, we introduce the papers that appear in this 50th anniversary issue, and consider the current state and the future of research in supply management, logistics, and the broader supply chain management discipline. In addition, we provide our own perspectives concerning the future direction of supply chain management research.

This is a book about Windows application development in C++. It addresses some rather difficult problems that occur during the development of advanced applications. Most books in this genre have many short code examples. This one has only four main code examples, but rather extensive ones. They are presented in increasing complexity order. The simplest one is the Tetris application, which deals with graphics, timing, and message handling. The Draw application adds a generic coordinate system and introduces more complex applications states. The Calc application deals with formula interpretation and graph searching. Finally, in the Word application every character is allowed to hold its own font and size, resulting in a rather complex size and position calculation. The book starts with an introduction to object-oriented programming in C++, followed by an overview of the Visual Studio environment with the Ring demonstration application as well as a presentation of some basic generic classes. Then the main applications are presented in one chapter each. What This Book Covers Chapter1. Introduction to C++-C++ is a language built on C. It is strongly typed; it has types for storing single as well as compound values. It supports dynamic memory management with pointers. It has a large set of operators to perform arithmetic, logical, and bitwise operations. The code can be organized into functions, and there is a pre-processor available, which can be used to define macros. Chapter 2. Object-oriented Programming in C++-C++ is an object-oriented language that fully supports the object-oriented model. The main feature of the language is the class, which can be instantiated into objects. A class can inherit another class. The inheritance can be virtual, which provides dynamic binding. A class can contain an object or have a pointer to another object. We can overload operators and we can throw exceptions. We can create generic classes by using templates and we can organize our classes into namespaces.

This paper discusses how the equivalent attribute technique (EAT) can be used to improve the comprehensibility of a multi-attribute utility theory study. When using EAT, 'vague' expected total utility values are converted into equivalent values for one of the attributes being considered, often an economic attribute. Two models are considered: a simplified linear model, and a more advanced non-linear model that includes the DM's strength-of-preference and risk attitude. EAT is particularly useful in distinguishing between alternatives with similar utility values. When the difference between utility values is larger, the choice among the alternatives should be clear, and EAT therefore becomes less useful. The technique can still be used, although extra care is needed when choosing the equivalent attribute. A local energyplanning problem is used as a case study to illustrate and exemplify the EAT approach.

The purpose of this research was to identify flexible and rigid pavements in Ohio with average and above average performance, and determine reasons for these differences in performance. The identification and implementation of factors linked to extended service life will improve performance statewide. FWD and ride quality profiles were measured to evaluate project uniformity, and material samples were obtained from a selected location on each project and tested in the laboratory to determine material properties. Volume 1 of the report includes: the project selection process, FWD and ride quality data, laboratory results of testing on base, subgrade and asphalt concrete pavement samples, and projected services lives using FWD data and the MEPDG. Volume 2 provides the results of laboratory tests and petrographic examinations on the Portland cement concrete cores. Volume 3 contains petrographic analysis of PCC pavement specimens in Cuyahoga County, Ohio containing Blast Furnace Slag Aggregate. Flexible and rigid pavements in Ohio receiving no structural maintenance show an average condition rating of 68 after 20 and 30 years of service, respectively. This performance, coupled with no structural distress being observed on the pavements selected for study indicates pavement design procedures used in Ohio are meeting expectations. Among the items recommended to improve pavement performance include: 1) maintaining subgrade uniformity to minimize localized failures, 2) reducing amounts of Portland cement and using larger aggregate in 451 and 452 concrete, while continuing to test aggregate for D-cracking susceptibility, 3) increasing emphasis on ensuring that dowel bars maintain proper alignment during placement of PC concrete, and 4) continuing the use of performance grading and polymers when designing AC mixes on heavily traveled pavements. Other observations regarding the data used to reach these conclusions include: keeping the PMIS database current, retaining construction records for at least the design life of the pavements, being aware that the effect of surface cracks on flexible pavement performance depends upon whether the cracks are top-down or bottom-up, and the PMIS and straight-line diagrams should be consistent in identifying project limits, project numbers and paving materials. Volume 2 of the report contains petrographic analysis of PCC pavement specimens.

Choosing a particular good or service always depends on the utility that we can expect from it. In different activities, a moment arrives when we need to choose one specific function, object, material, or generally, an entity, comparing to other similar entities based on the maximum efficiency that can be obtained with the least expenses of inputs. In economics, there are two famous problems on this same situation, namely, the Expenditure Minimization Problem (EmP) and the Utility Maximization Problem (UMP). However, there is a solution curve to both of these problems and when the curves of the individual functions attain monotonicity, we obtain a solution of UMP and EmP. This work focuses on establishing a generalized function for computing maximized utility of a function with minimum expenses. Further it gives a suitable approach that can be used to find the best finite bundle of products for a consumer.

In procurement, balancing costs with contract execution performance is key. Our study evaluates a unique experiment where scoring auctions were used with price weighed against the quality of past works rather than future ones. Results indicate a significant increase in performance-from 25% to 90%-across all audited parameters, but, paradoxically, no price increase. Using a symmetric auction model, we show that this is possible, especially when the market is characterized by quality concerns. We use structural estimation to quantify this phenomenon.

The paper presents some aspects of a customable Fuzzy e-Negotiation Agents (FeNAs) system for autonomous multi-issue negotiation in the presence of limited common knowledge and imprecise/soft constraints and preferences. The FeNAs use the principles of utility theory and fuzzy constraint-based reasoning in order to find a consensus that maximizes the agent's utility at the highest possible level of fuzzy constraint satisfaction subject to its acceptability by other agents. A scenario for negotiating document translation services is used to illustrate FeNAs' capabilities for multi-issue integrative negotiation. * The common knowledge can be explicit (e.g. information about private constraints, preferences, utilities etc may be disclosed by fully cooperative agents) or implicit (e.g. agents may have available some information about probability distribution of utilities of other agents).

In this paper, we describe an approach to allocation of function that makes use of scenarios as its basic unit of analysis. Our use of scenarios is driven by a desire to ensure that allocation decisions are sensitive to the context in which the system will be used and by insights from economic utility theory. We use the scenarios to focus the attention of decision makers on the relative costs and benefits of developing automated support for the activities of the scenario, the relative impact of functions on the performance of the operator's primary role and on the relative demands placed on an operator within the scenario. By focussing on relative demands and relative costs, our method seeks to allocate the operator's limited resources to the most important and most productive tasks within the work system, and to direct the effort of the design organisation to the development of automated support for those functions that deliver the greatest benefit for the effective operation of the integrated human-machine system.

This paper estimates the risk preferences of cotton farmers in Southern Peru, using the results from a multiple-price-list lottery game. Assuming that preferences conform to two of the leading models of decision under risk|Expected Utility Theory (EUT) and Cumulative Prospect Theory (CPT)|we nd strong evidence of moderate risk aversion. Once we include individual characteristics in the estimation of risk parameters, we observe that farmers use subjective nonlinear probability weighting, a behavior consistent with CPT. Interestingly, when we allow for preference heterogeneity via the estimation of mixture models|where the proportion of subjects who behave according to EUT or to CPT is endogenously determined|we nd that the majority of farmers' choices are best explained by CPT. We further hypothesize that the multiple switching behavior observed in our sample can be explained by nonlinear probability weighting made in a context of large random calculation mistakes; the evidence found on this regard is mixed. Finally, we nd that attaining higher education is the single most important individual characteristic correlated with risk preferences, a result that suggests a connection between cognitive abilities and behavior towards risk.

In any engineering decision-making process, it is a common problem to formulate a model with multiple objectives and to obtain proper answers. If the objectives are opposing, the problem then becomes finding the best possible design that identifies the best compromise between the opposing objectives. In a pavement management system of a state highway agency, engineers constantly struggle with performance requirements and limited budget. This situation results in an optimization problem with two conflicting objectives. The underlying algorithm of the classic network optimization system was coupled with genetic algorithm (GA) techniques to minimize budget and maximize performance of highway pavement networks in rehabilitation planning. GA is generally considered a powerful methodology in solving multiobjective problems. The data analysis demonstrated that the GA technique is applicable in producing workable solutions to a multiobjective pavement management problem.

I hereby declare that I'm the sole author of this thesis. This is a true copy of the thesis, including any required final revisions, as accepted by my examiners. I understand that my thesis may be made electronically available to the public.

Decisions are an important part of Concurrent Engineering and engineering design in general. Accordingly, more attention should be paid to the means and methods for making these decisions. In this article, a utility-based decision support method for the selection of an engineering design is presented. The utility-based selection decision support problem (u-sDSP) is a synthesized construct that facilitates selection decisions involving trade-offs among multiple, conflicting attributes and mitigation of risk associated with uncertain performance with respect to the attributes considered. The negative impact of unnecessary iterations on the product development cycle is reduced via the assurance of preference-consistent outcomes. Specifically, utility theory provides a mathematically rigorous means of clarifying and capturing designer preferences as well as identifying a preferred alternative in the context of stochastic uncertainty, while the selection decision support problem (DSP) – ...

We discuss a solution to the winner determination problem which takes into account not only costs but also risk aversion of the agent that accepts the bids. We are interested in bids for tasks that have time and precedence constraints. We develope an equivalent unit approach to the group of tasks to analyze the system and use Expected Utility Theory as the basic mechanism for decision-making. Our theoretical and experimental analysis shows that Expected Utility is especially useful for choosing between cheap-but-risky and costly-but-safe bids. Moreover, we show how bids with similar costs and similar probabilities of being successfully completed but different time windows can be efficiently selected or rejected.

In previous work we proposed an approach for computing an agent’s preferences over different schedules of tasks, and for soliciting desirable bid combinations to cover the tasks. The proposed approach finds schedules that maximize the agent’s Expected Utility. The maximization problem is hard because the domain is piece-wise continuous, with the number of pieces and local maxima growing exponentially in the worst case scenario. For agents who are averse to taking risks, maximization algorithms tend to converge to degenerate maxima of no practical interest. In this paper we demonstrate three maximization methods based on domain-specific heuristics. We also present a new stochastic maximization approach, and benchmark it in two substantially different problem setups. In this work we develop heuristics to overcome the maximization issues. We perform a comprehensive study of the domain’s properties using domain-specific heuristics and algorithms. We further use the obtained results to d...