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1

Nguyen, Dat-Dao. "Using Social Choice Function Vs. Social Welfare Function To Aggregate Individual Preferences In Group Decision Support Systems." International Journal of Management & Information Systems (IJMIS) 18, no. 3 (2014): 167. http://dx.doi.org/10.19030/ijmis.v18i3.8703.

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Анотація:
In multi-criteria decision making, any Group Decision Support System (GDSS) requires a social judgment model for calculation of weights on decision alternatives, and tabulation of individual votes toward a consensus. One could assess a Social Welfare Function - such as Keeneys - to aggregate individual cardinal preferences or utilities into a group preference. Alternatively, one could use Social Choice Functions - such as Condorcet, Borda, Copeland, and Eigenvector - to aggregate individual ordinal preferences or rankings into a group ranking. This study empirically investigates the consensus
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2

Khan, Mohammad Faisal, Md Gulzarul Hasan, Abdul Quddoos, Armin Fügenschuh, and Syed Suhaib Hasan. "Goal Programming Models with Linear and Exponential Fuzzy Preference Relations." Symmetry 12, no. 6 (2020): 934. http://dx.doi.org/10.3390/sym12060934.

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Goal programming (GP) is a powerful method to solve multi-objective programming problems. In GP the preferential weights are incorporated in different ways into the achievement function. The problem becomes more complicated if the preferences are imprecise in nature, for example ‘Goal A is slightly or moderately or significantly important than Goal B’. Considering such type of problems, this paper proposes standard goal programming models for multi-objective decision-making, where fuzzy linguistic preference relations are incorporated to model the relative importance of the goals. In the exist
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3

Knox, W. Bradley, Stephane Hatgis-Kessell, Sigurdur Orn Adalgeirsson, et al. "Learning Optimal Advantage from Preferences and Mistaking It for Reward." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 9 (2024): 10066–73. http://dx.doi.org/10.1609/aaai.v38i9.28870.

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We consider algorithms for learning reward functions from human preferences over pairs of trajectory segments, as used in reinforcement learning from human feedback (RLHF). Most recent work assumes that human preferences are generated based only upon the reward accrued within those segments, or their partial return. Recent work casts doubt on the validity of this assumption, proposing an alternative preference model based upon regret. We investigate the consequences of assuming preferences are based upon partial return when they actually arise from regret. We argue that the learned function is
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4

Zhou, Zhichun, David Burrell McAdam, Deborah Ann Napolitano, and Kathryn Douthit. "Shining a Light on the Challenging Behaviors of Adolescents with Comorbid Diagnoses: Use of Pictorial Concurrent Operant Preference Assessment." Children 8, no. 8 (2021): 683. http://dx.doi.org/10.3390/children8080683.

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Currently, there are no published studies that have used the concurrent operant preference assessment procedure to identify functions of challenging behaviors displayed by individuals with comorbid diagnoses. Four participants (aged 11–16 years) with comorbid diagnoses who displayed multiple challenging behaviors were referred to this study. We modified the standard concurrent operant preference assessment and used the new modified version, the pictorial concurrent operant preference assessment, to identify the functions of the challenging behaviors. Utilizing the triangulation mixed-methods d
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5

Weichselbaum, Hanna, Helmut Leder, and Ulrich Ansorge. "Implicit and Explicit Evaluation of Visual Symmetry as a Function of Art Expertise." i-Perception 9, no. 2 (2018): 204166951876146. http://dx.doi.org/10.1177/2041669518761464.

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In perception, humans typically prefer symmetrical over asymmetrical patterns. Yet, little is known about differences in symmetry preferences depending on individuals’ different past histories of actively reflecting upon pictures and patterns. To address this question, we tested the generality of the symmetry preference for different levels of individual art expertise. The preference for symmetrical versus asymmetrical abstract patterns was measured implicitly, by an Implicit Association Test (IAT), and explicitly, by a rating scale asking participants to evaluate pattern beauty. Participants
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6

Runken, Michael Chris, and Juan Marcos Gonzalez. "Using patients’ stated preferences for immunoglobulin therapies to evaluate administration features in current treatments." Journal of Immunology 196, no. 1_Supplement (2016): 130.5. http://dx.doi.org/10.4049/jimmunol.196.supp.130.5.

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Abstract In 2012, Mohamed et al.(J Med Econ) estimated preference weights for changes in the administration features of immunoglobulin (IG) therapies among patients with self-reported primary immunodeficiency disorder (PIDD). The preference weights were estimated using a discrete-choice experiment survey that asked respondents to choose between hypothetical treatments with varying administration features. However, the authors did not discuss the implications of their results on patients’ preferences for currently available IG therapies with specific combinations of the elicited features. Trans
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7

Ajaz, Taufeeq. "Nonlinear Reaction functions: Evidence from India." Journal of Central Banking Theory and Practice 8, no. 1 (2019): 111–32. http://dx.doi.org/10.2478/jcbtp-2019-0006.

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Abstract This paper uses time-series data from India and tests for asymmetries in policy preferences of the Reserve Bank of India (the Central Bank of India, hereafter RBI). The results show evidence in favour of preference asymmetries in monetary policy reaction function in India and hence nonlinearities in the Taylor-rule. Evidence of both recession avoidance preference (RAP) as well as inflation avoidance preference (IAP) is established. And it is found that RAP is dominant over IAP, thus confirming nonlinearities in reaction function which in the present case turns out to be concave in inf
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8

Akram, Muhammad, Shumaiza, and Ahmad N. Al-Kenani. "Multi-Criteria Group Decision-Making for Selection of Green Suppliers under Bipolar Fuzzy PROMETHEE Process." Symmetry 12, no. 1 (2020): 77. http://dx.doi.org/10.3390/sym12010077.

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Анотація:
The preference ranking organization method for enrichment of evaluations (PROMETHEE) method considers a significant outranking class of multi-criteria decision analysis (MCDA), as it is easy to deal with its simple computations. In the PROMETHEE, different preference functions are used according to the type and nature of attributes or criteria that demonstrate the clearness and reliability of this method. This study provides a new version of the PROMETHEE method using bipolar fuzzy information, named the bipolar fuzzy PROMETHEE method. Bipolar fuzzy sets or numbers constitute an asymmetrical r
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9

Chen, Yu-ke, Yan Zou, and Zhe Chen. "Preference Integration and Optimization of Multistage Weighted Voting System Based on Ordinal Preference." Abstract and Applied Analysis 2014 (2014): 1–6. http://dx.doi.org/10.1155/2014/186545.

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Multistage voting is a common voting form through which the winners are selected. By virtue of weighted multistage voting rules, in this paper, we establish a weighted voting model by analyzing the correlation between individual preference and group preference. The weights of voters in each voting stage are adjusted through preference deviation degrees between individual preferences and group preference, and the ranking among candidates in each stage is determined according to weighted Borda function value. Examples are given to verify our model, which shows that weighted information aggregati
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10

Esposito, Nicholas J. "Function as a Preferred Dimension among Children and Adults." Perceptual and Motor Skills 62, no. 3 (1986): 899–902. http://dx.doi.org/10.2466/pms.1986.62.3.899.

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Анотація:
Subjects' preferences for function vs form or for function vs color were tested using a method of triads. Children (16 girls, 24 boys) and adults (65 women, 17 men) showed a strong preference for function over color and adults also for function over form. Color-function concept identification was better when function was the relevant dimension. These data indicate that function can be assessed like physical dimensions, that function is more preferred than or as preferred as other dimensions by children and adults and that responses to preference tests are applicable over a wide range of dimens
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11

FEDRIZZI, MARIO, MICHELE FEDRIZZI, and R. A. MARQUES PEREIRA. "CONSENSUS MODELLING IN GROUP DECISION MAKING: DYNAMICAL APPROACH BASED ON FUZZY PREFERENCES." New Mathematics and Natural Computation 03, no. 02 (2007): 219–37. http://dx.doi.org/10.1142/s1793005707000744.

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Анотація:
The. notion of consensus plays an important role in group decision making, particularly when the collective preference structure is generated by a dynamical aggregation process of the single individual preference structures. In this dynamical process of aggregation each single decision maker gradually transforms his/her preference structure by combining it, through iterative weighted averaging, with the preference structures of the remaining decision makers. In this way, the collective decision emerges dynamically as a result of the consensual interaction among the various decision makers in t
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12

Diasakos, Theodoros M., and Georgios Gerasimou. "Preference Conditions for Invertible Demand Functions." American Economic Journal: Microeconomics 14, no. 2 (2022): 113–38. http://dx.doi.org/10.1257/mic.20190262.

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Анотація:
It is frequently assumed in several domains of economics that demand functions are invertible in prices. At the primitive level of preferences, however, the corresponding characterization has remained elusive. We identify necessary and sufficient conditions on a utility-maximizing consumer’s preferences for her demand function to be continuous and invertible: strict convexity, strict monotonicity, and differentiability in the sense of Rubinstein (2006). We further show that Rubinstein differentiability is equivalent to the indifference sets being smooth, which is weaker than Debreu’s (1972) no
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13

Diasakos, Theodoros M., and Georgios Gerasimou. "Preference Conditions for Invertible Demand Functions." American Economic Journal: Microeconomics 14, no. 2 (2022): 113–38. http://dx.doi.org/10.1257/mic.20190262.

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Анотація:
It is frequently assumed in several domains of economics that demand functions are invertible in prices. At the primitive level of preferences, however, the corresponding characterization has remained elusive. We identify necessary and sufficient conditions on a utility-maximizing consumer’s preferences for her demand function to be continuous and invertible: strict convexity, strict monotonicity, and differentiability in the sense of Rubinstein (2006). We further show that Rubinstein differentiability is equivalent to the indifference sets being smooth, which is weaker than Debreu’s (1972) no
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14

Dewitt, Barry, David Feeny, Baruch Fischhoff, et al. "Estimation of a Preference-Based Summary Score for the Patient-Reported Outcomes Measurement Information System: The PROMIS®-Preference (PROPr) Scoring System." Medical Decision Making 38, no. 6 (2018): 683–98. http://dx.doi.org/10.1177/0272989x18776637.

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Анотація:
Background. Health-related quality of life (HRQL) preference-based scores are used to assess the health of populations and patients and for cost-effectiveness analyses. The National Institutes of Health Patient-Reported Outcomes Measurement Information System (PROMIS®) consists of patient-reported outcome measures developed using item response theory. PROMIS is in need of a direct preference-based scoring system for assigning values to health states. Objective. To produce societal preference-based scores for 7 PROMIS domains: Cognitive Function–Abilities, Depression, Fatigue, Pain Interference
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15

Kilmer, J. T., K. D. Fowler-Finn, D. A. Gray, et al. "Describing mate preference functions and other function-valued traits." Journal of Evolutionary Biology 30, no. 9 (2017): 1658–73. http://dx.doi.org/10.1111/jeb.13122.

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16

ALESKEROV, FUAD T., and VYACHESLAV V. CHISTYAKOV. "THE THRESHOLD DECISION MAKING EFFECTUATED BY THE ENUMERATING PREFERENCE FUNCTION." International Journal of Information Technology & Decision Making 12, no. 06 (2013): 1201–22. http://dx.doi.org/10.1142/s021962201350034x.

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Based on the leximin and leximax preferences, we consider two threshold preference relations on the set X of alternatives, each of which is characterized by an n-dimensional vector (n ≥ 2) with integer components varying between 1 and m(m ≥ 2). We determine explicitly in terms of binomial coefficients the unique utility function for each of the two relations, which in addition maps X onto the natural 'interval' [Formula: see text], where [Formula: see text] is the quotient set of X with respect to the indifference relation I on X induced by the threshold preference. This permits us to evaluate
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17

Barzilai, Jonathan. "Measurement and preference function modelling." International Transactions in Operational Research 12, no. 2 (2005): 173–83. http://dx.doi.org/10.1111/j.1475-3995.2005.00496.x.

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18

Ullah, Khalil, and Muhammad Aslam. "Bayesian Analysis of the Weibull Paired Comparison Model Using Numerical Approximation." Journal of Mathematics 2020 (December 14, 2020): 1–6. http://dx.doi.org/10.1155/2020/6628379.

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Анотація:
The method of paired comparisons (PC) is widely used to rank items using sensory evaluations. The PC models are developed to provide basis for such comparisons. In this study, the Weibull PC model is analyzed under the Bayesian paradigm using noninformative priors and different loss functions, namely, Squared Error Loss Function (SELF), Quadratic Loss Function (QLF), DeGroot Loss Function (DLF), and Precautionary Loss Function (PLF). Numerical approximation is used to illustrate the entire estimation procedure. A real dataset showing usage preferences for different cellphone brands, Huawei (HW
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19

Anderson, Elizabeth. "Symposium on Amartya Sen's philosophy: 2 Unstrapping the straitjacket of ‘preference’: a comment on Amartya Sen's contributions to philosophy and economics." Economics and Philosophy 17, no. 1 (2001): 21–38. http://dx.doi.org/10.1017/s0266267101000128.

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Анотація:
The concept of preference dominates economic theory today. It performs a triple duty for economists, grounding their theories of individual behavior, welfare, and rationality. Microeconomic theory assumes that individuals act so as to maximize their utility – that is, to maximize the degree to which their preferences are satisfied. Welfare economics defines individual welfare in terms of preference satisfaction or utility, and social welfare as a function of individual preferences. Finally, economists assume that the rational act is the act that maximally satisfies an individual's preferences.
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20

Gao, Yang, Christian M. Meyer, and Iryna Gurevych. "Preference-based interactive multi-document summarisation." Information Retrieval Journal 23, no. 6 (2019): 555–85. http://dx.doi.org/10.1007/s10791-019-09367-8.

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AbstractInteractive NLP is a promising paradigm to close the gap between automatic NLP systems and the human upper bound. Preference-based interactive learning has been successfully applied, but the existing methods require several thousand interaction rounds even in simulations with perfect user feedback. In this paper, we study preference-based interactive summarisation. To reduce the number of interaction rounds, we propose the Active Preference-based ReInforcement Learning (APRIL) framework. APRIL uses active learning to query the user, preference learning to learn a summary ranking functi
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21

Lou, Xingzhou, Junge Zhang, Jian Xie, Lifeng Liu, Dong Yan, and Kaiqi Huang. "Sequential Preference Optimization: Multi-Dimensional Preference Alignment with Implicit Reward Modeling." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 26 (2025): 27509–17. https://doi.org/10.1609/aaai.v39i26.34963.

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Human preference alignment is critical in building powerful and reliable large language models (LLMs). However, current methods either ignore the multi-dimensionality of human preferences (e.g. helpfulness and harmlessness) or struggle with the complexity of managing multiple reward models. To address these issues, we propose Sequential Preference Optimization (SPO), a method that sequentially fine-tunes LLMs to align with multiple dimensions of human preferences. SPO avoids explicit reward modeling, directly optimizing the models to align with nuanced human preferences. We theoretically deriv
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22

Saidin Nainggolan, Yanuar Fitri, and Silvi Theresia. "Analysis of factors influencing production of rice farming and farmers preferences in addressing production risks in Tanjung Jabung Barat district, Jambi province." World Journal of Advanced Research and Reviews 20, no. 2 (2023): 649–55. http://dx.doi.org/10.30574/wjarr.2023.20.2.2055.

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Study This aim For analyze influencing factors production farming lowland rice and preferences farmer respond production farming paddy fields in Tanjung Jabung Barat Regency, Jambi Province. Locus study are Sriagung Village and Rawa Medang Village taken in a way purposive . Size sample as many as 91 respondents. Withdrawal method sample use simple random sampling method. Estimation function production use function production Cobb- Douglass. Approach method preference farmer respond risk production use method Moscardi and de Janvry. Determinant factors function production farming paddy fields a
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23

Mohsin, Ali, Qiong Shen, Xinyu Wang, and Xiaoming Zhang. "A Ranking Method for User Recommendation Based on Fuzzy Preference Relations in the Nature Reserve of Dangshan Pear Germplasm Resources." Information 9, no. 11 (2018): 291. http://dx.doi.org/10.3390/info9110291.

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Precision orchard management is an important avenue of investigation in agricultural technology and is an urgently needed part of information development in the fruit industry. Precision management based on a precision agricultural technology system involves many factors and results in users being unable to make accurate judgments. To improve user decision-making accuracy and the level of precision management, we used user preferences to achieve the recommendation function. In this paper, a ranking method based on fuzzy preference relations for user recommendation is proposed. We selected the
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24

Bradley, Gordon A., and Anne R. Kearney. "Public and Professional Responses to the Visual Effects of Timber Harvesting: Different Ways of Seeing." Western Journal of Applied Forestry 22, no. 1 (2007): 42–54. http://dx.doi.org/10.1093/wjaf/22.1.42.

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Abstract This study examines preferences and differences in preference among forest professionals and other forest stakeholders. Specifically, the study explores the underlying dimensions of preference and the stated rationale behind those preferences. Preferences were assessed for six different silvicultural treatments, including clearcutting, two-age cut, patch cut, group selection, commercial thin, and an unmodified control stand. Study participants were selected from six stakeholder groups: forest professionals, urban public, rural public, recreationists, environmentalists, and educators (
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25

Benabbou, Nawal, and Thibaut Lust. "A General Interactive Approach for Solving Multi-Objective Combinatorial Optimization Problems with Imprecise Preferences." Proceedings of the International Symposium on Combinatorial Search 10, no. 1 (2021): 164–65. http://dx.doi.org/10.1609/socs.v10i1.18472.

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In this paper, we develop a general interactive method to solve multi-objective combinatorial optimization problems with imprecise preferences. Assuming that preferences can be represented by a parameterized scalarizing function, we iteratively ask preferences queries to the decision maker in order to reduce the uncertainty over the preference parameters until being able to determine her preferred solution. To produce informative preference queries at each step, we generate promising solutions using the extreme points of the polyhedron representing the admissible preference parameters and then
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26

Saidin, Nainggolan, Fitri Yanuar, and Theresia Silvi. "Analysis of factors influencing production of rice farming and farmers preferences in addressing production risks in Tanjung Jabung Barat district, Jambi province." World Journal of Advanced Research and Reviews 20, no. 2 (2023): 649–55. https://doi.org/10.5281/zenodo.12590344.

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Анотація:
Study This aim For analyze influencing factors production farming lowland rice and preferences farmer respond production farming paddy fields in Tanjung Jabung Barat Regency, Jambi Province. Locus study are Sriagung Village and Rawa Medang Village taken in a way&nbsp;<em>purposive&nbsp;</em>. Size sample as many as 91 respondents. Withdrawal method sample use simple random sampling method. Estimation function production use function production&nbsp;<em>Cobb- Douglass</em>. Approach method preference farmer respond risk production use method&nbsp;<em>Moscardi and de Janvry</em>. Determinant fac
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27

Desjonquères, Camille, Rebecca R. Holt, Bretta Speck, and Rafael L. Rodríguez. "The relationship between a combinatorial processing rule and a continuous mate preference function in an insect." Proceedings of the Royal Society B: Biological Sciences 287, no. 1935 (2020): 20201278. http://dx.doi.org/10.1098/rspb.2020.1278.

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Анотація:
Mate choice involves processing signals that can reach high levels of complexity and feature multiple components, even in small animals with tiny brains. This raises the question of whether and how such organisms deal with this complexity. One solution involves combinatorial processing, whereby different signal elements are processed as single units. Combinatorial processing has been described in several mammals and birds, and recently in a vibrationally signalling insect, Enchenopa treehoppers. Here, we ask about the relationship between combinatorial rules and mate preferences for continuous
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28

McGuigan, Katrina, Anna Van Homrigh, and Mark W. Blows. "Genetic Analysis of Female Preference Functions as Function‐Valued Traits." American Naturalist 172, no. 2 (2008): 194–202. http://dx.doi.org/10.1086/588075.

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29

Eeckhoudt, Louis, and Harris Schlesinger. "Putting Risk in Its Proper Place." American Economic Review 96, no. 1 (2006): 280–89. http://dx.doi.org/10.1257/000282806776157777.

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This paper examines preferences toward particular classes of lottery pairs. We show how such concepts as prudence and temperance can be fully characterized by a preference relation over these lotteries. If preferences are defined in an expectedutility framework with differentiable utility, the direction of preference for a particular class of lottery pairs is equivalent to signing the nth derivative of the utility function. What makes our characterization appealing is its simplicity, which seems particularly amenable to experimentation.
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30

FOTSO, SIMEON, and LOUIS AIME FONO. "ON THE CONSISTENCY OF SOME CRISP CHOICE FUNCTIONS BASED ON A STRONGLY COMPLETE FUZZY PRE-ORDER." New Mathematics and Natural Computation 08, no. 02 (2012): 257–72. http://dx.doi.org/10.1142/s1793005712400145.

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Анотація:
This paper presents the first part of a general study of the structure of nine preference-based choice functions introduced by Barrett et al.2 More precisely, we show that, as for crisp total pre-orders, first and last alternatives exist in a finite set of alternatives equipped with a strongly complete fuzzy pre-order. We use that result to characterize each of those crisp choice functions for crisp total pre-orders and strongly complete fuzzy pre-orders. We study, by means of those characterizations, the consistency of those preference-based choice functions when preferences are strongly comp
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31

Kirkpatrick, Mark, and Maria R. Servedio. "The Reinforcement of Mating Preferences on an Island." Genetics 151, no. 2 (1999): 865–84. http://dx.doi.org/10.1093/genetics/151.2.865.

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Abstract We develop a haploid model for the reinforcement of female mating preferences on an island that receives migrants from a continent. We find that preferences will evolve to favor island males under a broad range of conditions: when the average male display trait on the island and continent differ, when the preference acts on that difference, and when there is standing genetic variance for the preference. A difference between the mean display trait on the continent and on the island is sufficient to drive reinforcement of preferences. Additional postzygotic isolation, caused, for exampl
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32

Maddulapalli, A. K., and S. Azarm. "Product Design Selection With Preference and Attribute Variability for an Implicit Value Function." Journal of Mechanical Design 128, no. 5 (2005): 1027–37. http://dx.doi.org/10.1115/1.2216728.

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Анотація:
An important aspect of engineering product design selection is the inevitable presence of variability in the selection process. There are mainly two types of variability: variability in the preferences of the decision maker (DM) and variability in attribute levels of the design alternatives. We address both kinds of variability in this paper. We first present a method for selection with preference variability alone. Our method is interactive and iterative and assumes only that the preferences of the DM reflect an implicit value function that is differentiable, quasi-concave and non-decreasing
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33

Zhu, Tianchen, Yue Qiu, Haoyi Zhou, and Jianxin Li. "Decoding Global Preferences: Temporal and Cooperative Dependency Modeling in Multi-Agent Preference-Based Reinforcement Learning." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 15 (2024): 17202–10. http://dx.doi.org/10.1609/aaai.v38i15.29666.

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Анотація:
Designing accurate reward functions for reinforcement learning (RL) has long been challenging. Preference-based RL (PbRL) offers a promising approach by using human preferences to train agents, eliminating the need for manual reward design. While successful in single-agent tasks, extending PbRL to complex multi-agent scenarios is nontrivial. Existing PbRL methods lack the capacity to comprehensively capture both temporal and cooperative aspects, leading to inadequate reward functions. This work introduces an advanced multi-agent preference learning framework that effectively addresses these li
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34

Matt, Vance, Carstens John, Gasper Michael, and Parker Phillip. "Quantitatively Exploring Human Preference." Journal of Management Science and Business Intelligence 3, no. 1 (2018): 15–30. https://doi.org/10.5281/zenodo.1246313.

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Анотація:
Qualitative preference is frequently used to make significant, programmatic choices between competing suppliers and products.&nbsp; Our research helped identify the degree of quantitative granularity, which must be present between criteria for defensible choices, by exploring how small of a difference humans are able to reliably perceive.&nbsp; The response options, the type of response option (either physical weight differentiation or web-based shape/size differentiation), and the granularity of these responses were the quantitative focus of our research.&nbsp; From this quantitative basis, w
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35

Gorka, Artur, and Phantipa Thipwiwatpotjana. "The Importance of Fuzzy Preference in Course Assignment Problem." Mathematical Problems in Engineering 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/106727.

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This paper points out the importance of fuzzy preference by using a teaching course assignment problem as a case study. The model with fuzzy teaching preference provides a more satisfactory solution to a course assignment problem than assigning arbitrary weights. A method for improving a fuzzy membership function by using sensitivity analysis is devised. The method with fuzzy preferences is compared with a model using weighted probabilities.
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36

Kaplan, Gisela, and Lesley J. Rogers. "Brain Size Associated with Foot Preferences in Australian Parrots." Symmetry 13, no. 5 (2021): 867. http://dx.doi.org/10.3390/sym13050867.

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Анотація:
Since foot preference of cockatoos and parrots to hold and manipulate food and other objects has been associated with better ability to perform certain tasks, we predicted that either strength or direction of foot preference would correlate with brain size. Our study of 25 psittacine species of Australia found that species with larger absolute brain mass have stronger foot preferences and that percent left-footedness is correlated positively with brain mass. In a sub-sample of 11 species, we found an association between foot preference and size of the nidopallial region of the telencephalon, a
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37

FRISCH, STEFAN, PETER BEIM GRABEN, and MATTHIAS SCHLESEWSKY. "PARALLELIZING GRAMMATICAL FUNCTIONS: P600 AND P345 REFLECT DIFFERENT COST OF REANALYSIS." International Journal of Bifurcation and Chaos 14, no. 02 (2004): 531–49. http://dx.doi.org/10.1142/s0218127404009533.

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Анотація:
It is well-known from psycholinguistic literature that the human language processing system exhibits preferences when sentence constituents are ambiguous with respect to their grammatical function. Generally, many theories assume that an interpretation towards the subject is preferred in such cases. Later disambiguations which contradict such a preference induce enhanced processing difficulty (i.e. reanalysis) which reflects itself in late positive deflections (P345/P600) in event-related brain potentials (ERPs). In the case of phoric elements such as pronouns, a second strategy is known accor
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38

Xu, Qianqian, Jiechao Xiong, Zhiyong Yang, Xiaochun Cao, Qingming Huang, and Yuan Yao. "Who Likes What? — SplitLBI in Exploring Preferential Diversity of Ratings." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 01 (2020): 262–69. http://dx.doi.org/10.1609/aaai.v34i01.5359.

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In recent years, learning user preferences has received significant attention. A shortcoming of existing learning to rank work lies in that they do not take into account the multi-level hierarchies from social choice to individuals. In this paper, we propose a multi-level model which learns both the common preference or utility function over the population based on features of alternatives to-be-compared, and preferential diversity functions conditioning on user categories. Such a multi-level model, enables us to simultaneously learn a coarse-grained social preference function together with a
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39

Wu, Chia-Ching, and Chien-Chung Chen. "Symmetry Modulates the Amplitude Spectrum Slope Effect on Visual Preference." Symmetry 12, no. 11 (2020): 1820. http://dx.doi.org/10.3390/sym12111820.

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Within the spectrum of a natural image, the amplitude of modulation decreases with spatial frequency. The speed of such an amplitude decrease, or the amplitude spectrum slope, of an image affects the perceived aesthetic value. Additionally, a human observer would consider a symmetric image more appealing than they would an asymmetric one. We investigated how these two factors jointly affect aesthetic preferences by manipulating both the amplitude spectrum slope and the symmetric level of images to assess their effects on aesthetic preference on a 6-point Likert scale. Our results showed that t
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40

Arntzen, Erik, and Mateusz Mysior. "Expansion of Classes, Transfer of Function, and Preference Tests in Adult Participants." Perspectivas em Análise do Comportamento 15, no. 2 (2024): xx. https://doi.org/10.18761/pac071024.

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The purpose of the experiment was to study the effect of transfer of function on preferences on different stimuli conditions in 15 adults. Participants were trained on six conditional discriminations arranged as one-to-many training (AB/AC) and tested for the emergence of three 3-member equivalence classes. Fourteen of 15 participants passed the equivalence test. For the 14 participants, the classes were expanded by training three new stimuli GOOD (D1), NEUTRAL (D2), and BAD (D3), to A1, A2, and A3 and followed by a test equivalence class formation including all relations. The participants wer
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41

Cheung, Stephen L. "Comment on “Risk Preferences Are Not Time Preferences”: On the Elicitation of Time Preference under Conditions of Risk." American Economic Review 105, no. 7 (2015): 2242–60. http://dx.doi.org/10.1257/aer.20120946.

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Andreoni and Sprenger (2012a, b) report evidence that distinct utility functions govern choices under certainty and risk. I investigate the robustness of this result to the experimental design. I find that the effect disappears completely when a multiple price list instrument is used instead of a convex time budget design. Alternatively, the effect is reduced by half when sooner and later payment risks are realized using a single lottery instead of two independent lotteries. The result is thus at least partially driven by intertemporal diversification, supporting an explanation in terms of con
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42

Kannan, Hanumanthrao, Garima V. Bhatia, Bryan L. Mesmer, and Benjamin Jantzen. "Theoretical Foundations for Preference Representation in Systems Engineering." Systems 7, no. 4 (2019): 55. http://dx.doi.org/10.3390/systems7040055.

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The realization of large-scale complex engineered systems is contingent upon satisfaction of the preferences of the stakeholder. With numerous decisions being involved in all the aspects of the system lifecycle, from conception to disposal, it is critical to have an explicit and rigorous representation of stakeholder preferences to be communicated to key personnel in the organizational hierarchy. Past work on stakeholder preference representation and communication in systems engineering has been primarily requirement-driven. More recent value-based approaches still do not offer a rigorous fram
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43

Okuyama, Teruhiro, Saori Yokoi, Hideki Abe, et al. "A Neural Mechanism Underlying Mating Preferences for Familiar Individuals in Medaka Fish." Science 343, no. 6166 (2014): 91–94. http://dx.doi.org/10.1126/science.1244724.

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Social familiarity affects mating preference among various vertebrates. Here, we show that visual contact of a potential mating partner before mating (visual familiarization) enhances female preference for the familiarized male, but not for an unfamiliarized male, in medaka fish. Terminal-nerve gonadotropin-releasing hormone 3 (TN-GnRH3) neurons, an extrahypothalamic neuromodulatory system, function as a gate for activating mating preferences based on familiarity. Basal levels of TN-GnRH3 neuronal activity suppress female receptivity for any male (default mode). Visual familiarization facilita
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44

Neelon, Daniel P., Rafael L. Rodríguez, and Gerlinde Höbel. "On the architecture of mate choice decisions: preference functions and choosiness are distinct traits." Proceedings of the Royal Society B: Biological Sciences 286, no. 1897 (2019): 20182830. http://dx.doi.org/10.1098/rspb.2018.2830.

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Mate choice is an important cause of sexual selection; it can drive the evolution of extravagant ornaments and displays, and promote speciation through the reproductive isolation generated by rapid divergence of sexual traits. Understanding mate choice requires knowledge of the traits involved in generating mate-choice decisions, and how those traits may interact with each other. It has been proposed that mate-choice decisions are the outcome of two components that vary independently: the preference function (the ranking of the attractiveness of prospective mates) and choosiness (the effort in
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45

Kim, Jin Bai, and Kern O. Kymn. "Rational choice function derived from a fuzzy preference." International Journal of Mathematics and Mathematical Sciences 11, no. 1 (1988): 43–45. http://dx.doi.org/10.1155/s0161171288000080.

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We shall prove that every fuzzy rational choice function is fuzzy regular (see Richter [6, p. 36] ), count the total number of the fuzzy rational choice ftmctions on a set of four elements and consider a semigroup of all fuzzy rational choice functions on a set.
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46

Rogers, Lesley J. "Development of Hand and Paw Preferences and Their Association with Other Patterns of Behaviour and Cognition." Symmetry 15, no. 4 (2023): 926. http://dx.doi.org/10.3390/sym15040926.

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Анотація:
Hand preference in non-human primates has been studied extensively with the aim of understanding the evolution of hemispheric asymmetry and hand preferences in humans. However, the focus has been on hand preferences expressed in adulthood, with a surprising lack of studies on hand preferences in infants and changes that occur during the development of other, potentially associated, asymmetries in the brain and behaviour. This paper reports on the development of hand preference for grasping food and taking it to the mouth in common marmosets. It considers the development of other types of behav
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47

Benabbou, Nawal, Cassandre Leroy, and Thibaut Lust. "An Interactive Regret-Based Genetic Algorithm for Solving Multi-Objective Combinatorial Optimization Problems." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 03 (2020): 2335–42. http://dx.doi.org/10.1609/aaai.v34i03.5612.

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Анотація:
We propose a new approach consisting in combining genetic algorithms and regret-based incremental preference elicitation for solving multi-objective combinatorial optimization problems with unknown preferences. For the purpose of elicitation, we assume that the decision maker's preferences can be represented by a parameterized scalarizing function but the parameters are initially not known. Instead, the parameter imprecision is progressively reduced by asking preference queries to the decision maker during the search to help identify the best solutions within a population. Our algorithm, calle
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48

Chen, Tinggui, Qianqian Li, Peihua Fu, et al. "Public Opinion Polarization by Individual Revenue from the Social Preference Theory." International Journal of Environmental Research and Public Health 17, no. 3 (2020): 946. http://dx.doi.org/10.3390/ijerph17030946.

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Social conflicts occur frequently during the social transition period and the polarization of public opinion happens occasionally. By introducing the social preference theory, the target of this paper is to reveal the micro-interaction mechanism of public opinion polarization. Firstly, we divide the social preferences of Internet users (network nodes) into three categories: egoistic, altruistic, and fair preferences, and adopt the revenue function to define the benefits obtained by individuals with different preferences among their interaction process so as to analyze their decision-making beh
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49

Xiao, Xingxing, and Jianzhong Li. "rkHit: Representative Query with Uncertain Preference." Proceedings of the ACM on Management of Data 1, no. 2 (2023): 1–26. http://dx.doi.org/10.1145/3589271.

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Анотація:
A top-k query retrieves the k tuples with highest scores according to a user preference, defined as a scoring function. It is difficult for a user to precisely specify the scoring function. Instead, obtaining the distribution on scoring functions, i.e., the preference distribution, has been extensively explored in many fields. Motivated by this, we introduce the uniform (r,k)-hit (UrkHit) problem. Given a preference distribution, UrkHit aims to select a representative set of r tuples to maximize the probability of containing a tuple attractive to the user. We say a tuple attracts a user, if it
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50

Jiang, Yiheng, Yuanbo Xu, Yongjian Yang, Funing Yang, Pengyang Wang, and Chaozhuo Li. "Auto Encoding Neural Process for Multi-interest Recommendation." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 11 (2025): 11879–87. https://doi.org/10.1609/aaai.v39i11.33293.

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Анотація:
Multi-interest recommendation constantly aspires to an oracle individual preference modeling approach, that satisfies the diverse and dynamic properties. Fueled by the deep learning technology, existing neural network (NN)-based recommender systems employ single-point or multi-point interest representation strategy to realize preference modeling,and boost the recommendation performance with a remarkable margin. However, as parameterized approximate functions, NN-based methods remain deficiencies with respect to the adaptability towards distinctive preference patterns cross different users and
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