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Individual choice behavior: A theoretical analysis.
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“This follows the Bradley-Terry model (Bradley and Terry, 1952) for estimating score functions from pairwise preferences, and is the specialization of the Luce-Shephard choice rule (Luce, 2005; Shepard, 1957) to preferences over trajectory segments.”
From Deep reinforcement learning from human preferences (2017) · cites this paper as Luce, 2005
In the citing paper
“Research into human choice suggests that both explicit and implicit choices systematically vary based on context, especially the other options that are present when choosing [56–59].”
From Evolution and impact of bias in human and machine learning algorithm interaction (2020) · cites this paper as [56]
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Salles, M., & Feng, Z. (2010) · Theory and decision library. Series C, Game theory, mathematical programming and operations research · doi:10.1007/978-3-642-02865-6_6 · Cited by 2
“Between transitivity of the relation 'at least as good as' and transitivity of the relation 'better than' (where the relation of indifference is not supposed to be transitive), two kinds of relations have been introduced: semi-orders and interval orders (Luce (1959, 2000), Suppes & al.”
BackgroundRiera, P., & Mogas, J. (2006) · Interciencia · Cited by 2
Albayrak, R. S. (2015) · Journal of Yaşar University · doi:10.19168/jyu.68036 · Cited by 2
Time and space order effetcs in timed brightness discrimination of paired visual stimuli
Patching, G. R., Englund, M. P., & Hellström, Å. (2008) · Lund University Publications (Lund University) · Cited by 2
Scaling of input forms by a simple pair comparison approach
Held, T., Fischer, P., & Schrepp, M. (2011) · Library Hi Tech · doi:10.1108/07378831111138206 · Cited by 2
The dynamics of social agreement according to Conceptual Agreement Theory
Canessa, E., & Chaigneau, S. E. (2013) · Quality & Quantity · doi:10.1007/s11135-013-9957-7 · Cited by 2
Energy Conservation and Rebates in Commercial Food Enterprises
Train, K. E., & Strebel, J. E. (1987) · American Journal of Agricultural Economics · doi:10.2307/1241311 · Cited by 2
A measure of trade centre position
Pina, I. P. A., & Aranda‐Gallego, J. (1998) · European Journal of Marketing · doi:10.1108/03090569810215858 · Cited by 2
A stochastic policy search model for matching behavior
Cheng, Z., Zhang, Y., & Deng, Z. (2011) · Science China Information Sciences · doi:10.1007/s11432-011-4304-x · Cited by 2
“…this stochastic choice is that the probability of selecting action a is determined by the policy parameter θ , as in the form of Luce choice rule [17] or softmax: and the policy parameter θ is updated by Let us examine the conditional probability P t ( x | θ ) to get an explicit formula for…”
BackgroundGroot, P. C., Heskes, T., Dijkstra, T. M. H., et al. (2010) · IEEE Transactions on Audio Speech and Language Processing · doi:10.1109/tasl.2010.2064311 · Cited by 2
Bridging Probabilistic and Fuzzy Approaches to Choice Under Uncertainty
Martinetti, D., Díaz, S., Montes, S., et al. (2013) · Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT) · doi:10.2991/eusflat.2013.126 · Cited by 2
“An interesting connection between the probabilistic and the fuzzy formalisms was established, in which Luce’s Choice Axiom played a key role.”
BackgroundInfluentialMultiproduct Pricing Management and Design of New Service Products
Wang, R. (2012) · doi:10.7916/d81v5mxd · Cited by 2
Applying Choice Based Conjoint Measurement to Forcast Demand for a New Restaurant Category
Carter, R., Dubelaar, C., & Wiley, J. B. (2001) · Journal of Food Products Marketing · doi:10.1300/j038v06n03_05 · Cited by 2
Quantification of product color preference in a utility function
Turner, H. L. (2010) · Cited by 2
The Multi-attribute Linear Ballistic Accumulator Model of Decision-making
Trueblood, J. S., Brown, S. D., & Heathcote, A. (2013) · eScholarship (California Digital Library) · Cited by 2
Formalizing Risky Choice with a Logistic Model of Fuzzy Trace Theory.
Broniatowski, D. A., & Reyna, V. F. (2015) · eScholarship (California Digital Library) · Cited by 2
A practical divide-and-conquer approach for preference-based learning to rank
Yang, H.-J., & Lin, H.-T. (2015) · Conference on Technologies and Applications of Artificial Intelligence (TAAI) · doi:10.1109/taai.2015.7407063 · Cited by 2
“We adopt the Bradley-Terry-Luce (BTL) model [30], [31] for our artificial data generation.”
MethodCozic, M. (2008) · Éditions de la Maison des sciences de l’homme eBooks · doi:10.4000/books.editionsmsh.9450 · Cited by 2
Grounding sound change in ideal observer models of perception
Burchill, Z., & Jaeger, T. F. (2017) · Workshop on Cognitive Modeling and Computational Linguistics (CMCL) · doi:10.18653/v1/w17-0703 · Cited by 2
“The general formulation of Equation (4) follows Luce and Pisoni (1998), using Luce’s choice rule—i.e. hearing each word out of all the alternatives at a probability equal to the probability that particular word (Luce, 1959).”
MethodApplication of List-Wise Rank Learning to Property Search for Renovation
Cheng, P.-C., Kobayashi, K., Hashimoto, T., Saito, K., & Takama, Y. (2017) · Conference on Technologies and Applications of Artificial Intelligence (TAAI) · doi:10.1109/taai.2017.11 · Cited by 2
“ListNet The ListNet algorithm is based on Plackett-Luce Model [7] [8].”
MethodTrade-Off Analysis for Eco-Tourism of the Tasik Kenyir Protected Area
Lola, M. S., Ramlee, M. N. A., Hussin, M. F., et al. (2018) · Springer eBooks · doi:10.1007/978-3-319-92264-5_21 · Cited by 2
Uncertain Choices: A Comparison of Fuzzy and Probabilistic Approaches
Martinetti, D., Montes, S., Díaz, S., et al. (2013) · Advances in intelligent systems and computing · doi:10.1007/978-3-642-39165-1_28 · Cited by 2
Top-k Ranking Bayesian Optimization
Nguyen, Q. P., Tay, S. S., Low, B. K. H., & Jaillet, P. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v35i10.17103 · Cited by 2
“When there is no tie (i.e., δ = 0 ), the model can be generalized to accept a ranking (i.e., x 1 (cid:31) x 2 (cid:31) · · · (cid:31) x m ) as an observation following the Plackett-Luce model (Luce 1959; Plackett 1975): In the following subsections, we introduce the notations for 2 different types of observation: top-…”
MethodModelling markets dynamics: Minority games and beyond
Challet, D., (ju, D. P., Yi-cheng, P., et al. (2000) · Cited by 2
Priorities in Thurstone Scaling and Steady-State Probabilities in Markov Stochastic Modeling
Lipovetsky, S. (2013) · Journal of Modern Applied Statistical Methods · doi:10.22237/jmasm/1367381460 · Cited by 2
“Together with the TMD model, the Bradley-Terry-Luce (BTL) model is also considered for pair comparison (Bradley & Terry, 1952; Luce (1959); Luce & Suppes, 1965; Lipovetsky, 2008) that corresponds to applying the logistic as opposed to the normal probability function.”
MethodUtilización de modelos matemáticos en psicología
Gras, J. A. (1977) · Anuario de Psicología/The UB Journal of Psychology · Cited by 2
Quantiative Social-Cognitive Experimental Pragmatics
Qing, C. (2014) · Cited by 2
Lower Bounds on the Bayes Risk of the Bayesian BTL Model With Applications to Comparison Graphs
Alsan, M., Prasad, R., & Tan, V. Y. F. (2018) · IEEE Journal of Selected Topics in Signal Processing · doi:10.1109/jstsp.2018.2827303 · Cited by 2
On Top-k Selection from m-wise Partial Rankings via Borda Counting
Chen, W., Zhou, R., Tian, C., & Shen, C. (2020) · IEEE International Symposium on Information Theory (ISIT) · doi:10.1109/isit44484.2020.9174020 · Cited by 2
Algorithmic Monoculture and Social Welfare
Raghavan, M. (2023) · ACM eBooks · doi:10.1145/3603195.3603211 · Cited by 2
Testing Preference Axioms in Discrete Choice experiments: A ReappraisalPreprint
Hougaard, J. L., Østerdal, L. P., & Tjur, T. (2006) · RePEc: Research Papers in Economics · Cited by 2
Government and Cities: Contests and the Decentralization of Decision MakingPreprint
Epstein, G. S., & Gang, I. N. (2002) · SSRN Electronic Journal · doi:10.2139/ssrn.323602 · Cited by 2
Sélection séquentielle en environnement aléatoire appliquée à l'apprentissage supervisé
Caelen, O., & Bontempi, G. (2009) · Dépôt institutionnel de l'Université libre de Bruxelles (Université Libre de Bruxelles) · Cited by 2
Commentary: “Neural signatures of intransitive preferences”
Brown, N., Davis‐Stober, C. P., & Regenwetter, M. (2015) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2015.00509 · Cited by 2
“Economists and psychologists have studied the conceptual challenges of taking a deterministic axiom like transitivity and expanding it into a probability model to incorporate the inherent uncertainty in human behavior (Luce, 1959; Block and Marschak, 1960; Luce and Narens, 1994; Loomes and Sugden, 1995; Hey, 2005).”
BackgroundReward information and cue selection following multiple-cue probability learning.
Allmeyer, D. H., & Medin, D. L. (1973) · Journal of Experimental Psychology · doi:10.1037/h0035220 · Cited by 2
Train, K. E., & Toyama, N. (1989) · The Energy Journal · doi:10.5547/issn0195-6574-ej-vol10-no1-8 · Cited by 2
Stochastic applications of media theory: Random walks on weak orders or partial orders
Falmagne, J., Hsu, Y., Leite, F. P., et al. (2007) · Discrete Applied Mathematics · doi:10.1016/j.dam.2007.04.032 · Cited by 2
Toscano, J. C., & McMurray, B. (2008) · The Journal of the Acoustical Society of America · doi:10.1121/1.4782535 · Cited by 2
“" Luce, R. D. (1959). Individual Choice Behavior: A Theoretical Analysis.”
MethodGaudry, M. J. I., & Quinet, É. (2012) · HAL (Le Centre pour la Communication Scientifique Directe) · Cited by 2
Misra, S., Roa, H. R., & Divakar, S. (2000) · IEEE Transactions on Systems Man and Cybernetics - Part A Systems and Humans · doi:10.1109/3468.895908 · Cited by 2
Surplus identification with non-linear returnsPreprint
Lunn, P., & Somerville, J. (2015) · RePEc: Research Papers in Economics · Cited by 2
Cerroni, S., Notaro, S., Raffaelli, R., et al. (2014) · SSRN Electronic Journal · doi:10.2139/ssrn.2405981 · Cited by 2
Mathematical Sociology: Some Educational and Organizational Problems of an Emergent Sub‐Discipline
Mayer, T. F. (1971) · International Journal of Mathematical Education in Science and Technology · doi:10.1080/0020739710020302 · Cited by 2
Learning RUMs: Reducing Mixture to Single Component via PCAPreprint
Devavrat Shah, B., & Song, D. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1812.11917 · Cited by 2
Boltzmann Exploration Expectation-MaximisationPreprint
Edman, M., & Dhir, N. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1912.08869 · Cited by 2
“Softmax action selection methods are based on Luce’s axiom of choice (Luce, 2012) and selects each arm (see definition 2.”
MethodInfluentialTwo-Sample Testing on Ranked Preference Data and the Role of Modeling AssumptionsPreprint
Rastogi, C., Balakrishnan, S., Shah, N. B., & Singh, A. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2006.11909 · Cited by 2
“Along with this, Plackett (1975) and Luce (1959) worked on the now-well-known Plackett-Luce model for partial and total rankings.”
MethodCompeting AI: How does competition feedback affect machine learning?Preprint
Ginart, A. A., Zhang, E., Kwon, Y., & Zou, J. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2009.06797 · Cited by 4
“…( y, ˆ y ( i ) ) / i ∈ [ k ] exp( − α(cid:96) ( y, ˆ y ( i ) )) This softmin model is commonly used to capture user decision making because it satisfies Luce’s choice axioms [1, 2, 3, 4] and emerges from the established information-theoretic notion of rational inattention in economics [5, 6, 7, 8].”
MethodDo Lottery Payments Induce Savings Behavior: Evidence from the LabPreprint
Filiz‐Ozbay, E., Guryan, J., Hyndman, K., et al. (2013) · RePEc: Research Papers in Economics · Cited by 2
Heterogeneous Rebound Effects: Comparing Estimates from Discrete-Continuous ModelsPreprint
Frondel, M., Flores, F. M., & Vance, C. (2016) · SSRN Electronic Journal · doi:10.2139/ssrn.2874901 · Cited by 2
Learnability and Stochastic ChoicePreprint
Basu, P. (2019) · SSRN Electronic Journal · doi:10.2139/ssrn.3338991 · Cited by 2
Tracing Systematic Errors to Personalize Recommendations in Single Digit Multiplication and BeyondPreprint
Savi, A. O., Deonovic, B., Bolsinova, M., van der Maas, H., & Maris, G. (2018) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/53muj · Cited by 5
“Importantly, assigning the obtained probabilities to the considered causes is in accordance with Luce’s choice axiom (Luce, 2005).”
ResultStrategic Mitigation of Agent Inattention in Drivers with Open-Quantum Cognition ModelsPreprint
Zhang, Q., Nadendla, V. S. S., Balakrishnan, S. N., et al. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2107.09888 · Cited by 2
A Theory of Tournament RepresentationsPreprint
Rajkumar, A., Veerathu, V., & Mir, A. B. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2110.05188 · Cited by 2
“A generalization of the classical Bradley-Terry-Luce model ([3], [12]) was studied in [4].”
MethodGeneralized Results for the Existence and Consistency of the MLE in the Bradley-Terry-Luce ModelPreprint
Bong, H., & Rinaldo, A. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2110.11487 · Cited by 2
“Among them, the renown Bradley-Terry-Luce (BTL) model (Bradley & Terry, 1952; Luce, 2012) has experienced a surge in popularity and use, due to its high interpretability and expressive power.”
BackgroundMethodGlobal visual salience of competing stimuliPreprint
Hernández-García, Á., Gameiro, R. R., Grillini, A., et al. (2019) · doi:10.31234/osf.io/z7qp5 · Cited by 2
The effect of social cues on marketing decisions
Hentschel, H. G. E., Pan, J., Family, F., et al. (2011) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2011.09.030 · Cited by 1
“Luce proposed the choice axiom [8] tomodel consumer choices without individual or social memories.”
BackgroundGoncharenko, A. (2022) · IEEE International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (TCSET) · doi:10.1109/tcset55632.2022.9766848 · Cited by 1
CrowdDC: Ranking From Crowdsourced Paired Comparison With Divide-and-Conquer
Wang, M.-H., Zhang, C.-Y., & Song, J.-R. (2023) · IEEE Transactions on Computational Social Systems · doi:10.1109/tcss.2023.3296632 · Cited by 1
“The BTL approach is a common statistical model used to predict the probability that one item is preferred over another when using paired comparisons to rank data [7], [12], [20].”
MethodExtreme Values and Choice Theory
Resnick, S. I., & Roy, R. (1994) · Springer eBooks · doi:10.1007/978-1-4613-3638-9_19 · Cited by 1
On the Existence of Low-Rank Explanations for Mixed Strategy Behavior
Barman, S., Bhaskar, U., Echenique, F., et al. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-13129-0_38 · Cited by 1
Vertical handover between wireless service providers
Mertikopoulos, P., Moustakas, A. L., & Dimitriou, N. (2008) · doi:10.1109/wiopt.2008.4586119 · Cited by 1
“To facilitate the players to converge to this equilibrial state, we propose an iterative scheme following the dynamics of the so-called logit model [10], in which each user rates the AI’s according to his connection satisfaction.”
MethodBaker, R., & McHale, I. G. (2012) · University of Salford Institutional Repository (University of Salford) · Cited by 1
Lara, C., Gómez, L., Valero, A., et al. (2013) · Revista Mexicana de Biodiversidad · doi:10.7550/rmb.31995 · Cited by 1
Lovie, S., & Lovie, P. (2004) · History of Psychology · doi:10.1037/1093-4510.7.3.248 · Cited by 1
Illustrative evaluation index for haptic interfaces using confusion matrices
Okamoto, S., & Yamada, Y. (2012) · doi:10.1109/roman.2012.6343881 · Cited by 1
“Powerful methods that compute inter-stimuli psychological distances from confusion matrices are the similarity choice model [9], [10] and overlap model [11], [12].”
MethodFraction-like ratings from preferential voting
Camps, R., Mora, X., & Saümell, L. (2015) · Publicacions Matemàtiques · doi:10.5565/publmat_59115_06 · Cited by 1
“Both Zermelo’s binary model and the ranking model that we are about to introduce can be viewed as special cases of a more general model, proposed in 1959 by Robert Duncan Luce, which considers the outcome of making a choice out of multiple options [15].”
MethodStatistik, F. (2013) · Cited by 1
Application of Game Theoretic Models to Evaluate Airline Equipage Dynamics of NextGen Technologies
Alonso, J. J., Bonnefoy, P. A., Bono, J. W., et al. (2013) · AIAA Aviation Technology, Integration, and Operations Conference (ATIO) · doi:10.2514/6.2013-4279 · Cited by 1
Prototype-based Knowledge Representation for an Improved Human-robot Interaction
Volkert, A., & Kirsch, A. (2016) · HAL (Le Centre pour la Communication Scientifique Directe) · doi:10.17185/duepublico/40717 · Cited by 1
“The first approach (Hampton, 1993), however, can be extended by a formula analogous to the one used in the second approach: Guaus i Termens (2009) proposed to use Luce’s Choice Rule (Luce, 1959) in order to decide, which is the most probable category of an item.”
MethodImproving document ranking with genetic and optimization algorithms
Master, L. (2017) · International Journal of Numerical Modelling Electronic Networks Devices and Fields · doi:10.1002/jnm.2310 · Cited by 1
“The permutation probability is calculated according to the Plackett‐Luce model.(23,24) To improve the efficiency of ListNet, the top one probability of an object is used.”
MethodRamlee, M. N. A., Lola, M. S., Rahman, M. N. A., et al. (2021) · Springer eBooks · doi:10.1007/978-3-030-64961-6_15 · Cited by 1
Sparse Communication via Mixed Distributions
Farinhas, A., Aziz, W. F., Niculae, V., & Martins, A. F. T. (2021) · UvA-DARE (University of Amsterdam) · doi:10.48550/arxiv.2108.02658 · Cited by 3
“When the temperature β approaches zero, the softmax approaches the indicator for argmax and Y becomes closer to a discrete categorical r.v. – this reparametrization of a categorical distribution is known as the Gumbel-max trick [Luce, 1959, Papandreou and Yuille, 2011].”
AI assurance using causal inference: application to public policy
Svetovidov, A., Rahman, A., & Batarseh, F. A. (2023) · Elsevier eBooks · doi:10.1016/b978-0-32-391919-7.00021-4 · Cited by 2
Mitigating Bias in Algorithmic Decision-making: Evaluating Claims and Practices
Raghavan, M. (2023) · ACM eBooks · doi:10.1145/3603195.3603212 · Cited by 1
Reward Learning With Intractable Normalizing Functions
Hoegerman, J., & Losey, D. P. (2023) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2023.3320009 · Cited by 1
“Prior work in behavioral economics [18], cognitive science [17], and reward learning [3] suggests that humans are noisily rational agents.”
BackgroundBoosting Feedback Efficiency of Interactive Reinforcement Learning by Adaptive Learning from Scores
Liu, S., Wu, C., Li, Y., & Zhang, L. (2023) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros55552.2023.10341990 · Cited by 1
“By following the Bradley-Terry and Luce-Shephard models of preferences [38], [39], a preference predictor using the reward function ˆ r θ can be modeled as a softmax-normalized distribution as follows. where τ i ≺ τ j denotes the trajectory τ j is more preferred to the trajectory τ j .”
MethodOptimizing Learning-to-Rank Models for Ex-Post Fair Relevance
Gorantla, S., Bhansali, E., Deshpande, A., & Louis, A. (2024) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3626772.3657751 · Cited by 1
LT2R: Learning to Online Learning to Rank for Web Search
Chu, X., Hao, C., Wang, S., Yin, D., Zhao, J., Zou, L., & Li, C. (2024) · IEEE International Conference on Data Engineering (ICDE) · doi:10.1109/icde60146.2024.00360 · Cited by 1
“Following the top-K assumption mentioned in Section II-B1a, the top-K ranking is generated by independently sampling K non-duplicated documents following Plackett-Luce distribution [41], [42].”
MethodOvert Visual Attention in the Formation of Preference Between Complex Lottery Options
Fan, X., Elsey, J., Wyngaard, A. J. G., Sampson, A. L., Yang, Y.-P., Emeric, E. E., Glickman, M., Usher, M., Levy, D. J., Stuphorn, V., et al. (2025) · Computational Brain & Behavior · doi:10.1007/s42113-025-00239-7 · Cited by 1
Probabilistic Choice with an Infinite Set of Options: An Approach Based on Random Sup Measures
Malmberg, H., & Hössjer, O. (2014) · EAA series · doi:10.1007/978-3-319-06653-0_18 · Cited by 1
“Random utility theory and probabilistic choice have for a long time been the standard tools for modelling discrete choice within the behavioural sciences [12, 15, 21].”
Bolker, E. D. (2016) · Cited by 1
A Rational Model for Individual Differences in Preference Choice
Ahmad, S., & Yu, A. J. (2015) · TUbilio (Technical University of Darmstadt) · Cited by 1
Leading the field: Fortune favors the bold in Thurstonian choice models
Evans, S. N., Rivest, R. L., & Stark, P. B. (2018) · Bernoulli · doi:10.3150/17-bej930 · Cited by 1
“The standard reference is Marden [1995], with Diaconis [1988], Fligner and Verducci [1993] as useful adjuncts.”
BackgroundSubirana, B., Perez-Sanchis, M., & Sarma, S. E. (2017) · IEEE International Conference on Intelligent Transportation Systems (ITSC) · doi:10.1109/itsc.2017.8317726 · Cited by 1
“First applied to psychology (as in [2]) and then extended to other areas including transport, discrete choice theory aims to understand, classify and predict how people make decisions when a discrete and finite set of options is presented to them.”
BackgroundA New Family of Fuzzy Discrete Choice Models
Aggarwal, M. (2019) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2019.2902108 · Cited by 1
“Luce choice axiom [2] is a popular model for the individual choice behavior, and is based on Thurstone’s principle of utility maximization.”
MethodGoncharenko, A. (2020) · Transactions of the Institute of Aviation · doi:10.2478/tar-2020-0004 · Cited by 1
“In such respect [1-40], the considered example may be given an attention to in regards with the MultiOptional Hybrid-Effectiveness Functions Uncertainty Measure Conditional Optimization Doctrine (method, approach, concept) applicable (used, implemented) to the aeronautical engineering optimal maintenance periodicities…”
BackgroundMethodComputable Approaches to Rational Choice and Decision-Making
Seo, H., & Thorson, S. J. (2021) · Hawaii International Conference on System Sciences (HICSS) · doi:10.24251/hicss.2021.171 · Cited by 1
The Hidden Assumptions Behind Counterfactual Explanations and Principal Reasons
Raghavan, M. (2023) · ACM eBooks · doi:10.1145/3603195.3603204 · Cited by 1
Cyber Object State Maximal Probability Timing Obtained Through Multi-Optional Technique.
Goncharenko, A. (2019) · Cited by 1
Blavatskyy, P. R. (2023) · Theory and Decision · doi:10.1007/s11238-023-09939-7 · Cited by 1
Characterizing and Predicting Early Reviewers for Effective Product Marketing on E-Commerce Websites
Chowdary, K., Babu, J. C., Khan, M., & Kiran, A. (2023) · International Conference on New Frontiers in Communication, Automation, Management and Security (ICCAMS) · doi:10.1109/iccams60113.2023.10526058 · Cited by 1
Interactions in DSGE Models: The Boltzmann-Gibbs Machine and Social Networks ApproachPreprint
Chang, C., & Chen, S. (2011) · SSRN Electronic Journal · doi:10.2139/ssrn.1973468 · Cited by 1
Pricing Bundles of Products and Services in the High-Tech Industry
Ferrer, J.-C. O. (2011) · DSpace@MIT (Massachusetts Institute of Technology) · Cited by 1
The Concrete Substrates of Abstract Rule Use
Love, B. C., Tomlinson, M. T., & Gureckis, T. M. (2008) · The Psychology of learning and motivation/The psychology of learning and motivation · doi:10.1016/s0079-7421(08)00005-4 · Cited by 1
An econometric examination of the adoption and use of microcomputers by Iowa farmers
Mercier, S. (1988) · doi:10.31274/rtd-180813-9315 · Cited by 1
Andriotti, G. K., & Klügl, F. (2006) · Lecture notes in computer science · doi:10.1007/11872283_6 · Cited by 1
Revealed Incomplete Preferences Under Uncertainty
Cettolin, E., & Riedl, A. M. (2015) · Journal of Economic Theory · doi:10.1016/j.jet.2019.03.002 · Cited by 66
Response hierarchy changes resulting from learning additional associations.
McConkie, G. W. (1969) · Journal of Experimental Psychology · doi:10.1037/h0026915 · Cited by 1
Optimal product line design workflows using a service oriented architecture
Tsafarakis, S., Delias, P., & Matsatsinis, N. F. (2010) · International Conference on Intelligent Systems Design and Applications (ISDA) · doi:10.1109/isda.2010.5687296 · Cited by 1
“These parameters are stored into a database, so that multiple services have access to them.”
Background
Metadata
- Authors
- Luce, R. D.
- Affiliations
- University of California, Irvine (US)
- Corresponding author
- Luce, R. Duncan
- Venue
- Dover Publications eBooks
- Publisher
- Dover Publications
- Published
- 2005
- OpenAlex
- W2094536313
- Cited by
- 1,157
- References
- 0
- Citations by year
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- FWCI
- 20.89
- Type
- book
- Language
- en
- Open access
- closed
- Locations
- Dover Publications eBooks (publishedVersion)
- Funders
- National Science Foundation (NSF-G2803)
- Office of Naval Research (G-4506)
- Topics
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Economic Theory and Institutions
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Experimental Behavioral Economics Studies
- Keywords
- decision-making, choice theory, consumer behavior, utility maximization
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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