Publications related to Rational choice theory

Exploring Spatial Perspective Taking in Human-Robot Interaction

Humans often rely on their perspective taking skills to thrive within the world's complex relations and connections. An adequate understanding of others' spatial perspectives can increase the quality of the interaction, not only perceptually but also cogni ...

EPFL2021

Motivating Innovation: The Effect of Loss Aversion on the Willingness to Persist

Kenneth Younge

We investigate the willingness of individuals to persist at exploration in the face of failure. Prior research suggests that the organization's "tolerance for failure" may motivate greater exploration by the individual. Little is known, however, about how ...

MIT Press2020

On the usefulness of mixed logit models with unobserved inter-and intra-individual heterogeneity

Michel Bierlaire, Prateek Bansal

Mixed logit models with unobserved inter- and intra-individual heterogeneity hierarchically extend standard mixed logit models by allowing tastes to vary randomly both across individuals as well as across choice tasks encountered by the same individual. Re ...

EPFL2020

Wasserstein Distributionally Robust Learning

Soroosh Shafieezadeh Abadeh

Many decision problems in science, engineering, and economics are affected by uncertainty, which is typically modeled by a random variable governed by an unknown probability distribution. For many practical applications, the probability distribution is onl ...

EPFL2020

Information Theoretic Characterization of Uncertainty Distinguishes Surprise From Accuracy Signals in the Brain

Leyla Loued-Khenissi, Kerstin Preuschoff

Uncertainty presents a problem for both human and machine decision-making. While utility maximization has traditionally been viewed as the motive force behind choice behavior, it has been theorized that uncertainty minimization may supersede reward motivat ...

2020

Classification of Metal-Based Drugs according to Their Mechanisms of Action

Paul Joseph Dyson

Metal-based drugs and imaging agents are extensively used in the clinic for the treatment and diagnosis of cancers and a wide range of other diseases. The current clinical arsenal of compounds operate via a limited number of mechanisms, whereas new putativ ...

CELL PRESS2020

Estimation of discrete choice models with hybrid stochastic adaptive batch size algorithms

Michel Bierlaire, Timothy Michael Hillel, Virginie Janine Camille Lurkin, Gael Lederrey

The emergence of Big Data has enabled new research perspectives in the discrete choice community. While the techniques to estimate Machine Learning models on a massive amount of data are well established, these have not yet been fully explored for the esti ...

2020

Anterior insula reflects surprise in value-based decision-making and perception

Leyla Loued-Khenissi, Kerstin Preuschoff

The brain has been theorized to employ inferential processes to overcome the problem of uncertainty. Inference is thought to underlie neural processes, including in disparate domains such as value-based decision-making and perception. Value-based decision- ...

2020

Courtesy As a Means to Coordinate

Boi Faltings, Panayiotis Danassis

We investigate the problem of multi-agent coordination under rationality constraints. Specifically, role allocation, task assignment, resource allocation, etc. Inspired by human behavior, we propose a framework (CA^3NONY) that enables fast convergence to e ...

International Foundation for Autonomous Agents and Multiagent Systems2019

Rationally almost periodic sequences, polynomial multiple recurrence and symbolic dynamics

Florian Karl Richter

A set

R\subset \mathbb{N}

is called rational if it is well approximable by finite unions of arithmetic progressions, meaning that for every

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there exists a set

B=\bigcup _{i=1}^{r}a_{i}\mathbb{N}+b_{i}

, where $a_{1},\ldots ,a_ ...

2019

Rational choice theory

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Exploring Spatial Perspective Taking in Human-Robot Interaction

Motivating Innovation: The Effect of Loss Aversion on the Willingness to Persist

On the usefulness of mixed logit models with unobserved inter-and intra-individual heterogeneity

Wasserstein Distributionally Robust Learning

Information Theoretic Characterization of Uncertainty Distinguishes Surprise From Accuracy Signals in the Brain

Classification of Metal-Based Drugs according to Their Mechanisms of Action

Estimation of discrete choice models with hybrid stochastic adaptive batch size algorithms

Anterior insula reflects surprise in value-based decision-making and perception

Courtesy As a Means to Coordinate

Rationally almost periodic sequences, polynomial multiple recurrence and symbolic dynamics

Exploring Spatial Perspective Taking in Human-Robot Interaction

Motivating Innovation: The Effect of Loss Aversion on the Willingness to Persist

Rationally almost periodic sequences, polynomial multiple recurrence and symbolic dynamics

Information Theoretic Characterization of Uncertainty Distinguishes Surprise From Accuracy Signals in the Brain

Classification of Metal-Based Drugs according to Their Mechanisms of Action

Wasserstein Distributionally Robust Learning

Estimation of discrete choice models with hybrid stochastic adaptive batch size algorithms

Anterior insula reflects surprise in value-based decision-making and perception

On the usefulness of mixed logit models with unobserved inter-and intra-individual heterogeneity

Courtesy As a Means to Coordinate