Descripción del proyecto
Un modelo informático de la toma de decisiones secuenciales humana en condiciones de incertidumbre
Las personas realizan actividades durante el día que requieren la coordinación de la percepción, la atención, la cognición, la planificación y la acción en un entorno cambiante y lleno de incertidumbres. La comprensión de las bases neurobiológicas de cada uno de estos elementos ha progresado mucho, en contraste con el conocimiento sobre cómo funcionan en conjunto dichos elementos. La toma de decisiones secuenciales óptimas en condiciones de incertidumbre se ha estudiado mucho en diversos campos como, por ejemplo, en las matemáticas y la estadística, la informática y la robótica, y las ciencias cognitivas. El equipo del proyecto ACTOR, financiado con fondos europeos, empleará este método para investigar y modelizar acciones secuenciales que impliquen condiciones de incertidumbre perceptual, variabilidad de la acción, costes y beneficios internos y externos, desde las más simples hasta las más complejas.
Objetivo
Imagine navigating through your kitchen, walking around your table and chairs, reaching the counter, sliding a cup on the countertop, pouring yourself some coffee, and preparing a sandwich. Such an every-day situation requires a sequence of behaviors involving the sophisticated interplay of perception, attention, cognition, planning, and action, all unfolding in an ambiguous and uncertain world. Yet, although past research in the behavioral sciences has revealed many properties of these constituent faculties, the understanding of how humans coordinate these cognitive abilities when carrying out every-day tasks is still rudimentary.
The goal of this project is to carry out behavioral experiments and develop computational models to identify and characterize perception, cognition, and action in the wild. Our hypothesis is, that sequential actions involving perceptual uncertainty, action variability, internal and external costs and benefits can be understood and modeled in the unified framework of optimal sequential decision making under uncertainty. To achieve this goal, we integrate ideas and methods from psychophysics, statistical decision theory, active vision, intuitive physics, optimal control under uncertainty, navigation, and inverse reinforcement learning. The proposal is structured in such a way that subsequent work packages consider tasks with increasing naturalness, from classical psychophysical production tasks, visuomtor control, to navigation and sandwich making. We will develop methods that allow recovering subjects’ perceptual uncertainties, beliefs about tasks, their subjective costs and benefits including effort, and action variability. Based on our previous experimental work on visuomotor behavior and theoretical work in modeling such behavior on an individual-by-individual and trial-by-trial basis, we seek to elucidate, how perception, cognition, and action are inseparably intertwined in extended, sequential behavior.
Ámbito científico
Programa(s)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Régimen de financiación
HORIZON-AG - HORIZON Action Grant Budget-BasedInstitución de acogida
64289 Darmstadt
Alemania