Journal
SYNTHESE
Volume 200, Issue 2, Pages -Publisher
SPRINGER
DOI: 10.1007/s11229-022-03480-w
Keywords
Active inference; Folk psychology; Predictive processing; Bayesian beliefs; Desires
Categories
Funding
- William K. Warren Foundation
- National Institute of General Medical Sciences [P20GM121312]
- Social Sciences and Humanities Research Council of Canada [756-2020-0704]
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This article addresses the potential tension between active inference and the belief-desire-intention (BDI) model within folk psychology. It distinguishes between active inference formulations of motor control, which do not require desires, and active inference formulations of decision processes, which do involve desires. Despite an initial conflict at the mathematical level, the active inference framework contains terms that encode both the objects and strength of desire at the psychological level. Simple simulations demonstrate how active inference can enhance folk-psychological descriptions and provide more precise predictions.
Active inference offers a unified theory of perception, learning, and decision-making at computational and neural levels of description. In this article, we address the worry that active inference may be in tension with the belief-desire-intention (BDI) model within folk psychology because it does not include terms for desires (or other conative constructs) at the mathematical level of description. To resolve this concern, we first provide a brief review of the historical progression from predictive coding to active inference, enabling us to distinguish between active inference formulations of motor control (which need not have desires under folk psychology) and active inference formulations of decision processes (which do have desires within folk psychology). We then show that, despite a superficial tension when viewed at the mathematical level of description, the active inference formalism contains terms that are readily identifiable as encoding both the objects of desire and the strength of desire at the psychological level of description. We demonstrate this with simple simulations of an active inference agent motivated to leave a dark room for different reasons. Despite their consistency, we further show how active inference may increase the granularity of folk-psychological descriptions by highlighting distinctions between drives to seek information versus reward-and how it may also offer more precise, quantitative folk-psychological predictions. Finally, we consider how the implicitly conative components of active inference may have partial analogues (i.e., as if desires) in other systems describable by the broader free energy principle to which it conforms.
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