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Mathematical Models of Decision Making Processes: State of the Art and Challenges

  • Fechas:

    Del 18/10/18 al 19/10/18

  • Lugar:

    Salón de Grados, Facultad de Psicología,Campus de Somosaguas, Madrid, España (mapa)

Web del evento

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In memoriam Julio Olea (1961 - 2018)

 

Video recordings of all sessions are linked in the program.

 

 


 

October 18 - 19, 2018

 

Presentation

 

Every action comes out of a choice. The cognitive mechanisms that govern these choices and the social, political, and economic patterns that emerge from them have been a subject of interest for behavioral scientists across disciplines. In this context, Psychology is concerned with explaining how decisions are made based on evidence, personal preferences, and individual criteria. Thus, formalizing human decision strategies, including a variety of biases and heuristics, is pivotal in understanding almost any human behavior.

 

Because of their ubiquity, decision-making processes hold particular relevance in experimental psychology, but they are often overlooked. Observers’ responses to experimental tasks are customarily taken as direct measures of the cognitive phenomenon of interest, even though decision processes unavoidably mediate those responses. Disregarding the decisional biases and judgment errors that take place during data collection has been shown to obscure theoretically relevant patterns and to contaminate them via methodological artifacts. Our success in developing meaningful theories about any aspect of human cognition is, thus, heavily dependent on our ability to devise dependable explanations of choice mechanisms. Mathematical modelling has proven to be helpful in disentangling the effects of the various psychological processes that mediate observed performance.

 

This seminar brings together seven renowned specialists who can offer a state-of-the-art view of quantitative decision-making models across different psychological domains, with a focus on three prominent frameworks within Mathematical Psychology: axiomatic choice models, perceptual decision-making models, and quantum cognition. Presentations will be followed by a discussion aimed at highlighting equivalences, connections, and distinctions among the different frameworks, also acknowledging the different challenges they face.

 

We hope to provide researchers with tools to address the study of decision processes, as well as present them with promising modeling paradigms that receive little attention in undergraduate and graduate Psychology programs.



Rocío Alcalá-Quintana

Berenice López-Casal

(Coordinators)


 

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Programa ↑ subir

El programa está disponible para descargas en este enlace.

 

 

October 18
  Session I: Axiomatic Choice

10:00

Opening session
10:30
Median responses, modal choices, prior parameters: How not to test theories of decision making
Michel Regenwetter (University of Illinois)
11:30 Coffee break
12:00
Linking Axiomatic Perspectives on Decision Making to Brain Connectivity
Clintin P. Davis-Stober (University of Missouri)
13:00 Lunch break
  Session II: Perceptual Decision Making
14:00
Decision processes in psychophysical tasks
Miguel A. García-Pérez (Universidad Complutense)
15:00
A two-stage diffusion model account for compelled-response task data
Adele Diederich (Jacobs University Bremen)
  October 19
  Session III: Quantum Cognition
10:00
What Is Quantum Cognition, and How Is It Applied to Psychology?
Jerome Busemeyer (Indiana University Bloomington)
11:00
Empirical Foundations of Quantum Cognition
Zheng Joyce Wang (The Ohio State University)
12:00 Coffee break
12:30
The rational (?) status of the conjunction fallacy
Emmanuel Pothos (City, University of London)
13:30
Discussion

 

Ponentes ↑ subir

Michel Regenwetter (University of Illinois)

Descripción

 

Clintin P. Davis-Stober (University of Missouri)

Descripción

 

Miguel A. García-Pérez (Universidad Complutense de Madrid)

Descripción

 

Adele Diederich (Jacobs University Bremen)

Descipción

 

Jerome Busemeyer (Indiana University-Bloomington)

Descripción

 

Zheng Joyce Wang (The Ohio State University)

Descripción

 

Emmanuel Pothos (City University London)

Descripción

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