Individual Choice Behavior: A Theoretical Analysis.
By V. Cane, R. Luce. 1960
Subfields: Game & Decision Theory, Cognitive Science & Psychology
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Game & Decision Theory
- Hannes Malmberg
- Paulo Natenzon
- Róbert Istvan Busa-Fekete
- Adil El Mesaoudi-Paul
- Marco Mariotti
- Doina Precup
- Chao Gao
- Naoki Masuda
In Cognitive Science & Psychology
- Michael I. Jordan
- T. Griffiths
- Dharshan Kumaran
- Jerome R. Busemeyer
- James L. McClelland
- Hannes Malmberg
- Paulo Natenzon
- Róbert Istvan Busa-Fekete
Citations in the corpus
- Generalized Results for the Existence and Consistency of the MLE in the Bradley-Terry-Luce Model (2021, methodology): “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.”
- The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables (2016, methodology): “ DISCRETE RANDOM VARIABLES AND THE GUMBEL-MAX TRICK To motivate the construction of Concrete random variables, we review a method for sampling from discrete distributions called the Gumbel-Max trick (Luce, 1959; Yellott, 1977; Papandreou & Yuille, 2011; Hazan & Jaakkola, 2012; Maddison et al”
- Generalization Through the Recurrent Interaction of Episodic Memories (2012, methodology): “Choice probabilities were then determined by applying the Luce choice rule (equivalent to the softmax function; Luce, 1959) to the activity values of the relevant units in the response layer (e.”
- Extrapolating Beyond Suboptimal Demonstrations via Inverse Reinforcement Learning from Observations (2019, methodology): “This form of loss function follows from the classic Bradley-Terry and Luce-Shephard models of preferences (Bradley & Terry, 1952; Luce, 2012) and has been shown to be effective for training neural networks from preferences (Christiano et al., 2017; Ibarz et al., 2018).”
- Restricted Boltzmann machines modeling human choice (2014, background): “For example, Lemma 3 of [10] can tell us whether a given choice model satisfies the IIA in (16) for all cases or it violates the IIA for some cases to some degree.”
- A Nonparametric Approach to Modeling Choice with Limited Data (2009, background): “Talluri and van Ryzin (2004a), Gallego et al. (2006), van Ryzin and Vulcano (2008), Mahajan and van Ryzin (1999), Goyal et al. (2009) are all papers in this vein. Kök et al. (2008) provides an excellent overview of the state-of-the-art in assortment optimization.”
- Rational Inattention to Discrete Choices: A New Foundation for the Multinomial Logit Model (2015, unknown): “This alternative derivation of equation (13) is closely related to the Luce (1959) derivation of the standard multinomial logit model from the IIA axiom, which is an alternative derivation to the random utility derivation.”