Friston, K;
FitzGerald, T;
Rigoli, F;
Schwartenbeck, P;
O'Doherty, J;
Pezzulo, G;
(2016)
Active inference and learning.
Neuroscience and Biobehavioral Reviews
, 68
pp. 862-879.
10.1016/j.neubiorev.2016.06.022.
Preview |
Text
1-s2.0-S0149763416301336-main.pdf Download (5MB) | Preview |
Abstract
This paper offers an active inference account of choice behaviour and learning. It focuses on the distinction between goal-directed and habitual behaviour and how they contextualise each other. We show that habits emerge naturally (and autodidactically) from sequential policy optimisation when agents are equipped with state-action policies. In active inference, behaviour has explorative (epistemic) and exploitative (pragmatic) aspects that are sensitive to ambiguity and risk respectively, where epistemic (ambiguity-resolving) behaviour enables pragmatic (reward-seeking) behaviour and the subsequent emergence of habits. Although goal-directed and habitual policies are usually associated with model-based and model-free schemes, we find the more important distinction is between belief-free and belief-based schemes. The underlying (variational) belief updating provides a comprehensive (if metaphorical) process theory for several phenomena, including the transfer of dopamine responses, reversal learning, habit formation and devaluation. Finally, we show that active inference reduces to a classical (Bellman) scheme, in the absence of ambiguity.
Archive Staff Only
 |
View Item |
