Computational enactivism under the free energy principle
Synthese March 1, 2021 Peer reviewed DOI: 10.1007/s11229-019-02243-4
Summary
Enactivism and computationalism, two opposing approaches in cognitive science, can be reconciled using the free energy principle (FEP). FEP describes cognitive systems as encoding generative models of their environments, with cognition minimizing the free energy of those models. A computationalist interprets this as cognition being a computational process of Bayesian inference, while an enactivist sees it as systems self-organizing to maintain a non-equilibrium steady-state. The paper argues both interpretations are simultaneously true and mutually illuminating.
Study at a glance
| Design | theoretical or philosophical paper |
|---|---|
| Key finding | Enactivism and computationalism can be reconciled under the free energy principle, as both interpretations are simultaneously true and enlightening to each other. |
Abstract
AbstractIn this paper, I argue that enactivism and computationalism—two seemingly incompatible research traditions in modern cognitive science—can be fruitfully reconciled under the framework of the free energy principle (FEP). FEP holds that cognitive systems encode generative models of their niches and cognition can be understood in terms of minimizing the free energy of these models. There are two philosophical interpretations of this picture. A computationalist will argue that as FEP claims that Bayesian inference underpins both perception and action, it entails a concept of cognition as a computational process. An enactivist, on the other hand, will point out that FEP explains cognitive systems as constantly self-organizing to non-equilibrium steady-state. My claim is that these two interpretations are both true at the same time and that they enlighten each other.