Narrow Results

This paper explores the application of machine learning techniques for acquiring utility functions in message routing within Vehicular Ad Hoc Networks (VANETs), aiming to enhance the performance of message routing. Message routing in VANETs employs a store-carry-and-forward protocol, where vehicles (nodes) holding messages traverse suitable trajectories and opportunistically forward messages upon entering the communication range of other nodes. The core of the protocols involves context-dependent decision-making on whether to forward messages to an encountered node and, if so, determining which message to transmit. To enhance the message arrival to the destination with short delay, we introduce a method building upon Wu et al.’s prior work on utility function acquisition through the structure learning of Bayesian networks. Our proposed method incorporates two key innovations: (1) integrating destination information of forwarded messages as an attribute within the Bayesian network and (2) extending the crossover operation from genetic algorithms to optimize the attribute order in the structure learning. Through extensive experiments conducted on the ONE simulator, our method demonstrates superior utility compared to the existing baselines, showcasing its effectiveness in VANET message routing improvement.

A simulation software package (UFLibrary) implementing the utility function (UF) method for behavior selection in autonomous robots, is introduced and described by means of an example involving a simple exploration robot equipped with a repertoire of five different behaviors. The UFLibrary (as indeed the UF method itself) is aimed at providing a rapid yet reliable and generally applicable procedure for generating behavior selection systems for autonomous robots, while at the same time minimizing the amount of hand-coding related to the activation of behaviors. It is demonstrated how the UFLibrary allows a user to rapidly implement individual behaviors and to set up and carry out simulations of a robot in its arena, in order to generate and optimize, by means of an evolutionary algorithm, the behavior selection system of the robot.

We re-take the possibilistic (as opposed to probabilistic) approach to information coding put forward in ^1,2. To enhance the possibilistic approach also outside the realm of "subjective" uncertainties, in this paper we adopt an "objective" interpretation of possibilistic source coding based on utility functions and an "objective" interpretation of possibilistic channel coding based on distortion measures and similarity indices. We stress the relationship between possibilistic coding as based on distortions between sequences and algebraic coding as based on minimum distances between codewords. We compute the operational (coding-theoretic) entropy for a new class of possibilistic sources.

In this paper, the weighted quasi-arithmetic means are discussed from the viewpoint of utility functions and downward risks in economics. Representing the weighting functions by probability density functions and the conditional expectations, an index for downward risks in stochastic environments is derived. This paper discusses the relation among the index, the first-order stochastic dominance and the risk premium in economics, and further it investigates the relation between the index and value-at-risks which are known as another estimation for downward risks in finance. Finally, this paper shows a lot of examples of the weighted quasi-arithmetic mean and the aggregated mean ratio for various typical utility functions with various typical utility functions and probability density functions.

In the traditional decision theory, choice with undetermined consequence is usually regarded as random variable, which usually describes objective uncertainty. This paper first considers the human uncertainty in making decisions, and employs uncertain variable to describe the choice. Utility function is also employed in the paper, and expected utility is introduced as a criterion to rank the choices. At last, in order to illustrate the uncertain decision making method, a portfolio selection problem is considered.

In this paper we deal with the optimization problem of maximizing the expected total utility from consumption under the case of partial information. By means of the martingale method and filter theory, we have acquired an explicit solution to optimal investment and consumption determined by the security prices for a special security price process. Furthermore, we establish a simple formula for valuing information, provided that the utility function is logarithmic. In the end, we extend most of the conclusions to a general situation where both the interest rate and dispersion coefficient of risk security follow some stochastic processes.

We measure the performance of probabilistic models from a decision-theoretic perspective along the lines of Friedman and Sandow [6]. In particular, we adopt the point of view of an investor who evaluates models based on the test-sample averaged utility of the expected-utility-optimal strategies that the models suggest in the horse race setting. In this paper, we relax the assumptions of Friedman and Sandow [6]: we omit the notion of a "true" measure and we allow our investor to withhold or borrow cash, which widens the range of possible applications. We show that, in this setting, our relative model performance measure is odds-ratio independent if and only if the investor has a generalized logarithmic utility function, in which case it essentially reduces to the likelihood ratio. We also show that for horse races with nearly homogeneous returns, our relative performance measure is approximately equal to the likelihood ratio.

In this paper, we study the Kelly criterion in the continuous time framework building on the work of E.O. Thorp and others. The existence of an optimal strategy is proven in a general setting and the corresponding optimal wealth process is found. A simple formula is provided for calculating the optimal portfolio in terms of drift, short term risk-free rate and correlations for a set of generic multi-dimensional diffusion processes satisfying some simple conditions. Properties of the optimal investment strategy are studied. The paper ends with a short discussion of the implications of these ideas for financial markets.

In this paper, we consider the portfolio optimization problem in a financial market where the underlying stochastic volatility model is driven by n-dimensional Brownian motions. At first, we derive a Hamilton–Jacobi–Bellman equation including the correlations among the standard Brownian motions. We use an approximation method for the optimization of portfolios. With such approximation, the value function is analyzed using the first-order terms of expansion of the utility function in the powers of time to the horizon. The error of this approximation is controlled using the second-order terms of expansion of the utility function. It is also shown that the one-dimensional version of this analysis corresponds to a known result in the literature. We also generate a close-to-optimal portfolio near the time to horizon using the first-order approximation of the utility function. It is shown that the error is controlled by the square of the time to the horizon. Finally, we provide an approximation scheme to the value function for all times and generate a close-to-optimal portfolio.

This paper attempts to adapt the value-focused thinking approach to the decision problems in the field of environmental management of buildings construction. A qualitative value model based on the results of life cycle assessment is presented. The model is applied on a case study in which a decision should be made on three types of roof structures: wood, steel and concrete. It is found that the roof structure made of wood is the most compatible option with respect to the environmental requirements of buildings construction. Thus, the value-focused thinking model can be used in different situations to analyze what management actions will be most effective to maximise the fulfillment of the environmental requirements of building standards.

In this paper, an attempt is made to present a method to assess the sustainable development of a region. The method is based on adapting the multi-attribute utility theory to the concept of "composite indicator" of the region under concern; a composite indicator represents a weighted number of components or sub-indicators. Comparisons are made with the standard method of ranking and the axiomatic multi-criteria method. It is shown that the suggested method is more practical and feasible as it allows the studying of the potential improvement that can be performed in order to heighten the status of the sustainable development of a region, in the long and short run. Finally, a tentative quantitative index to evaluate the sustainability of a region is proposed.

In this chapter, we first discuss utility theory and utility function in detail, then we show how asset allocation can be done in terms of the quadratic utility function. Based upon these concepts, we show Markowitz’s portfolio selection model can be executed by constrained maximization approach. Real world examples in terms of three securities are also demonstrated. In the Markowitz selection model, we consider that short sale is both allowed and not allowed.

In this chapter, we first discuss utility theory and utility function in detail, then we show how asset allocation can be done in terms of quadratic utility function. Based upon these concepts, we show that Markowitz’s portfolio selection model can be executed by the constrained maximization approach. Real-world examples in terms of three securities are also demonstrated. In the Markowitz selection model, we consider that short sale is both allowed and not allowed.

We give some conditions satisfied by the solution of utility maximization problems under several constraints, with incomes normalized to one. We generalize the one constraint Slutsky conditions in consumer theory. We note that the necessary conditions are not sufficient in contrary to the one constraint case.

The following sections are included:

• INTRODUCTION

• FOUR KEY ELEMENTS OF A DECISION

• DECISIONS BASED ON EXTREME VALUES
  • Maximin Criterion
  • Minimax Regret Criterion

• EXPECTED MONETARY VALUE AND UTILITY ANALYSIS
  • The Expected Monetary Value Criterion
  • Utility Analysis

• BAYES STRATEGIES
  • Bayesian Approach in Forecasting Interest Rates

• DECISION TREES AND EXPECTED MONETARY VALUES
  • A Decision Tree for Testing a Drilling Site
  • A Decision Tree for Capital Budgeting
  • Utilizing Sample Information to Improve the Determination of Pricing Policy⁴

• MEAN AND VARIANCE TRADE-OFF ANALYSIS
  • The Mean–Variance Rule and the Dominance Principle
  • The Capital Market Line
  • The Capital Asset Pricing Model

• THE MEAN AND VARIANCE METHOD FOR CAPITAL BUDGETING DECISIONS
  • Statistical Distribution of Cash Flow

• Summary

• Appendix 21A Using the Spreadsheet in Decision-Tree Analysis

• Appendix 21B Graphical Derivation of the Capital Market Line

• Appendix 21C Present Value and Net Present Value
  • Present Value
  • Net Present Value

• Appendix 21D Derivation of Standard Deviation for NPV

• Questions and Problems

• Project V Project for Selected Topics in Statistical Analysis

We survey a number of financial settings linked by the importance of a reference point in the decision making process. For each of them, we discuss how the reference points affect the decisions. We conclude that it is not a coincidence that reference points are essential to many financial settings. Reference points boost the incentives of the individuals, which we argue is the reason why they are so prevalent. Stronger incentives lead to more effort, which leads to higher achievement and the desire for more reference point-based decisions.

In this paper, we study the Kelly criterion in the continuous time framework building on the work of E.O. Thorp and others. The existence of an optimal strategy is proven in a general setting and the corresponding optimal wealth process is found. A simple formula is provided for calculating the optimal portfolio for a set of price processes satisfying some simple conditions. Properties of the optimal investment strategy for assets governed by multiple Ornstein-Uhlenbeck processes are studied. The paper ends with a short discussion of the implications of these ideas for financial markets.