Choix

Résumé

Un choix résulte de la décision d'un individu ou d'un groupe confronté à une situation ou à un système offrant une ou plusieurs options. Le terme « choix » pouvant désigner le processus par lequel cette opération est menée à bien et/ou le résultat de ladite opération :

en philosophie, la question de savoir si un individu effectue des choix librement ou est déterminé renvoie au problème de l'existence ou non du libre arbitre. De plus, l’expression « être un Renaud » prend de l’ampleur dans le langage utilisé par les 18-25ans. Fondée en 2020 en l’hommage au pionnier des mauvaises decision Thomas Renaud, est utilisée pour décrire des personnes qui font une succession de mauvais choix dans leur vie. Exemple : garer sa voiture entre deux blocs de béton armée trop serrés entraînant une forte détérioration d’un véhicule ;
en théorie des automates, une machine pouvant effectuer un choix, généralement parmi un nombre fini de solutions, est appelée automate non déterministe. Les capacités

Source officielle

https://fr.wikipedia.org/wiki/Choix

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Cours associés (26)

The course allows students to get familiarized with the basic tools and concepts of modern microeconomic analysis. Based on graphical reasoning and analytical calculus, it constantly links to real economic issues.

Discrete choice models allow for the analysis and prediction of individuals' choice behavior. The objective of the course is to introduce both methodological and applied aspects, in the field of marketing, transportation, and finance.

Since 2010 approaches in deep learning have revolutionized fields as diverse as computer vision, machine learning, or artificial intelligence. This course gives a systematic introduction into influential models of deep artificial neural networks, with a focus on Reinforcement Learning.

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Séances de cours associées (42)

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The Window : A guided Choice between Physics and Ecology

1997

Chargement

Exploiting pedestrian WiFi traces for destination choice modeling

Loïc Tinguely

My master thesis proposes a general methodology to model pedestrian destination choice from WiFi localization in multimodal transport facilities (e.g., airports, railway stations). It is based on the output of [Danalet, A., B. Farooq and M. Bierlaire (2014) A Bayesian approach to detect pedestrian destination-sequences from WiFi signatures, Transportation Research Part C: Emerging Technologies, 44, 146–170.] method to generate candidates of activity-episode sequences from WiFi measurements, locations of activities on a map and prior information. Destination choice is nested to the activity choice. An individual first chooses an activity ([Danalet, A. and M. Bierlaire (2015) Importance sampling for activity path choice, paper presented at the 15th Swiss Transport Research Conference (STRC), Monte Verità, Ascona, Switzerland.]), and then selects the destination where to perform it. We propose an approach to model destination choice accounting for panel nature of data. We compare static, dynamic strict exogenous and dynamic model with two different agent effect corrections inspired by [Wooldridge, J. M. (2002) Simple solutions to the initial conditions problem in dynamic, nonlinear panel data models with unobserved heterogeneity, Journal of applied econometrics, 44, ISSN 1753-9196.] method. In a case study using WiFi traces on EPFL campus, we focus on one activity type: catering. The choice set contains 21 alternatives on campus (restaurants, self-services, cafeterias, ...). Our models reveal that the choice of a catering facility depends mostly on habits (e.g., where an individual ate the previous time), distance to walk from the previous activity-episode (calculated with a weighted shortest path algorithm) but less on destination specific determinants (e.g., price, capacity). The models are successfully validated using the same WiFi dataset and we forecast possible changes concerning catering destinations on the campus.

2015

Chargement

Device-to-Device Assisted Video Transmission

Laura Toni, Wenwen Zhou

To increase spectrum efficiency, researchers envi- sion a device-to-device (D2D) communication system in which a closely located mobile device pair may share the same spectrum with a cellular user. By opportunistically choosing the frequency, the D2D pair may increase the spectrum efficiency in terms of data rate per Hertz, at the price of additional interference to that cellular user. In previous models, users either stop cellular transmission and switch to D2D transmission or vice versa. However, if the cell is fully loaded, a D2D pair will not be able to switch back to the conventional mode because no extra resource is available. In this paper, we propose a D2D assisted model, where a D2D link is enabled to assist transmission, while keeping the conventional cellular transmission. In this way, the D2D link can be turned on and off according to the link quality. We also propose a PHY-layer study for the transmission scheme in such a way that the system throughput and the video reception quality is always improved compared to a conventional link.

2013

Chargement

Exploiting pedestrian WiFi traces for destination choice modeling

Loïc Tinguely

2015