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Journal ArticleDOI

Modeling a Decision-Maker’s Choice Behavior Through Perceived Values

01 Mar 2021-IEEE Transactions on Systems, Man, and Cybernetics (IEEE)-Vol. 51, Iss: 3, pp 1933-1944
TL;DR: The proposed choice models are augmented with the parameters of an entropy function, besides the utility coefficients, to model a DM's complex choice behavior and are further extended with a DM’s reference-value for each attribute.
Abstract: In the real world, an attribute value is perceived differently by different individuals. Emphasizing on this aspect, we extend the discrete choice models with perceived values that are subjective and specific to a decision-maker (DM). The proposed choice models are augmented with the parameters of an entropy function, besides the utility coefficients, to model a DM’s complex choice behavior. A variety of higher order choice models are also proposed. The proposed models are further extended with a DM’s reference-value for each attribute. A real and illustrative application is included.
Citations
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Posted Content
TL;DR: The main advances regarding the use of the Choquet and Sugeno integrals in multi-criteria decision aid over the last decade are reviewed in this paper, mainly a bipolar extension of both Choquet integral and the Sugeno integral.
Abstract: The main advances regarding the use of the Choquet and Sugeno integrals in multi-criteria decision aid over the last decade are reviewed. They concern mainly a bipolar extension of both the Choquet integral and the Sugeno integral, interesting particular submodels, new learning techniques, a better interpretation of the models and a better use of the Choquet integral in multi-criteria decision aid. Parallel to these theoretical works, the Choquet integral has been applied to many new fields, and several softwares and libraries dedicated to this model have been developed.

449 citations

09 Mar 2023
TL;DR: In this paper , a novel bias-embedded preference model called Probe is proposed, which incorporates a weight function to capture users' projection bias and a value function to account for the reference-point effect, and introduce prospect theory from behavioral economics to combine the weight and value functions.
Abstract: Intertemporal choices involve making decisions that require weighing the costs in the present against the benefits in the future. One specific type of intertemporal choice is the decision between purchasing an individual item or opting for a bundle that includes that item. Previous research assumes that individuals have accurate expectations of the factors involved in these choices. However, in reality, users' perceptions of these factors are often biased, leading to irrational and suboptimal decision-making. In this work, we specifically focus on two commonly observed biases: projection bias and the reference-point effect. To address these biases, we propose a novel bias-embedded preference model called Probe. The Probe incorporates a weight function to capture users' projection bias and a value function to account for the reference-point effect, and introduce prospect theory from behavioral economics to combine the weight and value functions. This allows us to determine the probability of users selecting the bundle or a single item. We provide a thorough theoretical analysis to demonstrate the impact of projection bias on the design of bundle sales strategies. Through experimental results, we show that the proposed Probe model outperforms existing methods and contributes to a better understanding of users' irrational behaviors in bundle purchases. This investigation can facilitate a deeper comprehension of users' decision-making mechanisms, enable the provision of personalized services, and assist users in making more rational and optimal decisions.
References
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Book
01 Jan 2020
TL;DR: In this article, the authors present a comprehensive introduction to the theory and practice of artificial intelligence for modern applications, including game playing, planning and acting, and reinforcement learning with neural networks.
Abstract: The long-anticipated revision of this #1 selling book offers the most comprehensive, state of the art introduction to the theory and practice of artificial intelligence for modern applications. Intelligent Agents. Solving Problems by Searching. Informed Search Methods. Game Playing. Agents that Reason Logically. First-order Logic. Building a Knowledge Base. Inference in First-Order Logic. Logical Reasoning Systems. Practical Planning. Planning and Acting. Uncertainty. Probabilistic Reasoning Systems. Making Simple Decisions. Making Complex Decisions. Learning from Observations. Learning with Neural Networks. Reinforcement Learning. Knowledge in Learning. Agents that Communicate. Practical Communication in English. Perception. Robotics. For computer professionals, linguists, and cognitive scientists interested in artificial intelligence.

16,983 citations

01 Jan 1972

15,741 citations


Additional excerpts

  • ...Multinomial logit (MNL) [2] is a popular discrete choice model that predicts an individual’s choice probabilities....

    [...]

Book
01 Jan 2003
TL;DR: In this paper, the authors describe the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation, and compare simulation-assisted estimation procedures, including maximum simulated likelihood, method of simulated moments, and methods of simulated scores.
Abstract: This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logit, generalized extreme value, or GEV (including nested and cross-nested logits), probit, and mixed logit, plus a variety of specifications that build on these basics. Simulation-assisted estimation procedures are investigated and compared, including maximum simulated likelihood, method of simulated moments, and method of simulated scores. Procedures for drawing from densities are described, including variance reduction techniques such as anithetics and Halton draws. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. No other book incorporates all these fields, which have arisen in the past 20 years. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.

7,768 citations

Journal ArticleDOI
Ronald R. Yager1
03 Jan 1988
TL;DR: A type of operator for aggregation called an ordered weighted aggregation (OWA) operator is introduced and its performance is found to be between those obtained using the AND operator and the OR operator.
Abstract: The author is primarily concerned with the problem of aggregating multicriteria to form an overall decision function. He introduces a type of operator for aggregation called an ordered weighted aggregation (OWA) operator and investigates the properties of this operator. The OWA's performance is found to be between those obtained using the AND operator, which requires all criteria to be satisfied, and the OR operator, which requires at least one criteria to be satisfied. >

6,534 citations

Journal ArticleDOI
TL;DR: The law of comparative judgment as mentioned in this paper is applicable not only to the comparison of physical stimulus intensities but also to qualitative comparative judgments such as those of excellence of specimens in an educational scale.
Abstract: This chapter describes a new psychophysical law which may be called the law of comparative judgment and to show some of its special applications in the measurement of psychological values. The law of comparative judgment is applicable not only to the comparison of physical stimulus intensities but also to qualitative comparative judgments such as those of excellence of specimens in an educational scale. The scale difference between the discriminal processes of two specimens which are involved in the same judgment will be called the discriminal difference on that occasion. The law of comparative judgment is basic for all experimental work on Weber's law, Fechner's law, and for all educational and psychological scales in which comparative judgments are involved. The formulation of the law of comparative judgment involves the use of a new psychophysical concept, namely, the discriminal dispersion.

4,929 citations


Additional excerpts

  • ...Based on the utility maximization behavior [45], they give the probability for an alternative to be chosen by a decision-maker (DM), when faced with a set of competing alternatives....

    [...]