scholarly journals Least Concave Ordinal Utility Function and the Marshalian Cardinal Utility

2012 ◽  
Vol 4 (1) ◽  
pp. 9-16
Author(s):  
Taradas Bandyopadhyay ◽  
Tapan Biswas
Keyword(s):  
Utility Function ◽  
Utility Functions ◽  
Cardinal Utility ◽  
Ordinal Utility

This paper examines the conditions under which the Marshallian type of cardinal utility function can be derived from a class of ordinal utility functions.

DECISION ANALYSIS WITH MULTIPLE OBJECTIVES IN A FRAMEWORK FOR EVALUATING IMPRECISION

2005 ◽  
Vol 13 (05) ◽  
pp. 495-509 ◽  
Author(s):  
ARON LARSSON ◽  
JIM JOHANSSON ◽  
LOVE EKENBERG ◽  
MATS DANIELSON
Keyword(s):  
Decision Tree ◽  
Utility Function ◽  
Evaluation Method ◽  
Convex Sets ◽  
Utility Functions ◽  
Probability Measures ◽  
Decisions Under Risk ◽  
Closed Intervals ◽  
Pros And Cons ◽  
Tree Evaluation

We present a decision tree evaluation method for analyzing multi-attribute decisions under risk, where information is numerically imprecise. The approach extends the use of additive and multiplicative utility functions for supporting evaluation of imprecise statements, relaxing requirements for precise estimates of decision parameters. Information is modeled in convex sets of utility and probability measures restricted by closed intervals. Evaluation is done relative to a set of rules, generalizing the concept of admissibility, computationally handled through optimization of aggregated utility functions. Pros and cons of two approaches, and tradeoffs in selecting a utility function, are discussed.

scholarly journals Comparing utility functions between risky and riskless choice in rhesus monkeys

2021 ◽  
Author(s):  
Philipe M. Bujold ◽  
Simone Ferrari-Toniolo ◽  
Leo Chi U Seak ◽  
Wolfram Schultz
Keyword(s):  
Utility Function ◽  
Utility Theory ◽  
Utility Maximization ◽  
Choice Behavior ◽  
Expected Utility Theory ◽  
Utility Functions ◽  
Random Utility Maximization ◽  
Risky Choices ◽  
Neuronal Mechanisms ◽  
Subjective Value

AbstractDecisions can be risky or riskless, depending on the outcomes of the choice. Expected Utility Theory describes risky choices as a utility maximization process: we choose the option with the highest subjective value (utility), which we compute considering both the option’s value and its associated risk. According to the random utility maximization framework, riskless choices could also be based on a utility measure. Neuronal mechanisms of utility-based choice may thus be common to both risky and riskless choices. This assumption would require the existence of a utility function that accounts for both risky and riskless decisions. Here, we investigated whether the choice behavior of macaque monkeys in riskless and risky decisions could be described by a common underlying utility function. We found that the utility functions elicited in the two choice scenarios were different from each other, even after taking into account the contribution of subjective probability weighting. Our results suggest that distinct utility representations exist for riskless and risky choices, which could reflect distinct neuronal representations of the utility quantities, or distinct brain mechanisms for risky and riskless choices. The different utility functions should be taken into account in neuronal investigations of utility-based choice.

Power Law with Exponential Cut‐off Utility

Metamorphosis ◽  
2014 ◽  
Vol 13 (1) ◽  
pp. 26-32
Author(s):  
Afreen Arif H. ◽  
T.P.M. Pakkala
Keyword(s):  
Risk Aversion ◽  
Utility Function ◽  
Power Law ◽  
Risk Preferences ◽  
Portfolio Allocation ◽  
Utility Functions ◽  
Relative Risk Aversion ◽  
Optimal Solutions ◽  
New Class ◽  
Exponential Power

Most of the utility functions studied earlier concentrated on properties of risk aversion. In this article, the authors have introduced a new class of utility function called the Power Law with Exponential Cut-off (PLEC) utility function, which exhibits all the absolute and relative risk aversion and risk loving preferences of individuals, under various conditions. It generalises and encompasses other systems of utility functions like that of exponential power. Certain properties of this utility function are discussed. Sensitivity analysis exhibits different portfolio allocations for various risk preferences. The analysis also shows that arbitrary risk preferences may lead to biased risk response estimates. Performance of PLEC utility function in portfolio allocation problem is demonstrated through numerical examples. This is evaluated through optimal solutions.

Autonomous Vehicle-Target Assignment: A Game-Theoretical Formulation

2007 ◽  
Vol 129 (5) ◽  
pp. 584-596 ◽  
Author(s):  
Gürdal Arslan ◽  
Jason R. Marden ◽  
Jeff S. Shamma
Keyword(s):  
Utility Function ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Utility Functions ◽  
Fading Memory ◽  
Theoretical Formulation ◽  
Design Procedures ◽  
Target Assignment ◽  
Negotiation Mechanism ◽  
Adaptive Play

We consider an autonomous vehicle-target assignment problem where a group of vehicles are expected to optimally assign themselves to a set of targets. We introduce a game-theoretical formulation of the problem in which the vehicles are viewed as self-interested decision makers. Thus, we seek the optimization of a global utility function through autonomous vehicles that are capable of making individually rational decisions to optimize their own utility functions. The first important aspect of the problem is to choose the utility functions of the vehicles in such a way that the objectives of the vehicles are localized to each vehicle yet aligned with a global utility function. The second important aspect of the problem is to equip the vehicles with an appropriate negotiation mechanism by which each vehicle pursues the optimization of its own utility function. We present several design procedures and accompanying caveats for vehicle utility design. We present two new negotiation mechanisms, namely, “generalized regret monitoring with fading memory and inertia” and “selective spatial adaptive play,” and provide accompanying proofs of their convergence. Finally, we present simulations that illustrate how vehicle negotiations can consistently lead to near-optimal assignments provided that the utilities of the vehicles are designed appropriately.

The Use of Utility Functions for Investment Channel Choice in Defined Contribution Retirement Funds. II: A Proposed System

2003 ◽  
Vol 9 (4) ◽  
pp. 903-958 ◽  
Author(s):  
R. J. Thomson
Keyword(s):  
Stochastic Model ◽  
Utility Function ◽  
Stochastic Models ◽  
Utility Functions ◽  
Retirement Income ◽  
Defined Contribution ◽  
Channel Choice ◽  
Retirement Funds

ABSTRACTIn this paper a system for recommending investment channel choices to members of defined contribution retirement funds is proposed. The system is interactive, using a member's answers to a series of questions to derive a utility function. The observed values are interpolated by means of appropriate formulae to produce a smooth utility function over the whole positive range of benefits at retirement. The resulting function, together with stochastic models of the returns on the available channels and of the annuity factor at exit, is then used to recommend an optimum apportionment of the member's investment. The proposed system is applied to the observed values of utility functions of post-retirement income elicited from members of retirement funds. Difficulties in the application are discussed and the results are analysed. The sensitivity of the recommendations to the parameters of the stochastic model is discussed.

scholarly journals Cooter and Rappoport on the Normative

1990 ◽  
Vol 6 (1) ◽  
pp. 139-146 ◽  
Author(s):  
John B. Davis
Keyword(s):  
Research Agenda ◽  
Utility Theory ◽  
Economic Thought ◽  
Neoclassical Economics ◽  
Economic Science ◽  
Cardinal Utility ◽  
Ordinal Utility ◽  
Widespread Acceptance ◽  
The One ◽  
Interpersonal Utility Comparisons

In a recent examination of the origins of ordinal utility theory in neoclassical economics, Robert D. Cooter and Peter Rappoport argue that the ordinalist revolution of the 1930s, after which most economists abandoned interpersonal utility comparisons as normative and unscientific, constituted neither unambiguous progress in economic science nor the abandonment of normative theorizing, as many economists and historians of economic thought have generally believed (Cooter and Rappoport, 1984). Rather, the widespread acceptance of ordinalism, with its focus on Pareto optimality, simply represented the emergence of a new neoclassical research agenda that, on the one hand, defined economics differently than had the material welfare theorists of the cardinal utility school and, on the other, adopted a positivist methodology in contrast to the less restrictive empiricism of the cardinalists.

scholarly journals A Utility Function for Examining Policy Affecting Salmon on the Skeena River

1977 ◽  
Vol 34 (1) ◽  
pp. 49-63 ◽  
Author(s):  
Ralph L. Keeney
Keyword(s):  
Interest Groups ◽  
Utility Function ◽  
Utility Functions ◽  
Multiple Objectives ◽  
Utility Model ◽  
Multiattribute Utility ◽  
Utility Models ◽  
Constructive Discussion ◽  
Skeena River ◽  
Comparative Examination

The interests of many groups, some with multiple objectives, are important to include in evaluating strategies affecting salmon in the Skeena River. A multiattribute utility model is proposed for addressing these issues. Two first-cut utility functions are assessed using the preferences of two individuals familiar with the problem. These utility functions provide a basis for constructive discussion to arrive at a reasonable utility function for examining alternative policies. Two unique features of this study are the explicit focus on value tradeoffs and equity considerations among interest groups, and a comparative examination of the two first-cut multiattribute utility models. This examination indicates the range of fundamental preferences which can be captured using multiattribute utility functions and illustrates the potential of the theory for conflict illumination and resolution.

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