Synergizing habits and goals with variational Bayes.
Nat Commun
; 15(1): 4461, 2024 May 25.
Article
em En
| MEDLINE
| ID: mdl-38796491
ABSTRACT
Behaving efficiently and flexibly is crucial for biological and artificial embodied agents. Behavior is generally classified into two types habitual (fast but inflexible), and goal-directed (flexible but slow). While these two types of behaviors are typically considered to be managed by two distinct systems in the brain, recent studies have revealed a more sophisticated interplay between them. We introduce a theoretical framework using variational Bayesian theory, incorporating a Bayesian intention variable. Habitual behavior depends on the prior distribution of intention, computed from sensory context without goal-specification. In contrast, goal-directed behavior relies on the goal-conditioned posterior distribution of intention, inferred through variational free energy minimization. Assuming that an agent behaves using a synergized intention, our simulations in vision-based sensorimotor tasks explain the key properties of their interaction as observed in experiments. Our work suggests a fresh perspective on the neural mechanisms of habits and goals, shedding light on future research in decision making.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Teorema de Bayes
/
Objetivos
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Hábitos
Idioma:
En
Ano de publicação:
2024
Tipo de documento:
Article