@article{han2024synergizing,
author = {Han, Dongqi and Doya, Kenji and Li, Dongsheng and Tani, Jun},
title = {Synergizing habits and goals with variational Bayes},
year = {2024},
month = {May},
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.},
url = {http://approjects.co.za/?big=en-us/research/publication/synergizing-habits-and-goals-with-variational-bayes/},
journal = {Nature Communications},
}