The Game of Self: Identity and Experience as Active Inference

Academic AbstractActive inference is an integrative theoretical framework that models the nervous system as a statistical engine for predicting and regulating sensory input. Within this framework, perception and behavior work toward the same imperative: minimizing uncertainty. The current article extends this approach to the inferences social agents make about themselves as both subjects and objects of experience. The resulting model conceptualizes "The Game of Self" as a continuous Bayesian updating of episodic and semantic self-representations in order to reduce self-related uncertainty. The model proposes a bidirectional predictive loop that evolves over time-semantic representations of identity guide the construction of episodic experience, while those experiences, in turn, shape semantic self-categorization. In both directions, the self-representations that emerge through active inference are those with the highest posterior probabilities given situational evidence. The article explores how episodic and semantic self-representations are continuously shaped by a dynamic and adaptive process of Bayesian inference.Public AbstractWho am I? What am I feeling? What should I do? These are fundamental questions that people ask themselves throughout their lives-and the answers can shape everything from small decisions to major life changes. But how do we come to know ourselves in the face of social and personal uncertainty? This article examines how the brain uses statistical modeling to make sense of identity and experience in an uncertain world. It introduces the concept of "The Game of Self"-an ongoing cycle between who we think we are and what we're experiencing. Our beliefs about who we are shape what we experience, and our experiences shape who we think we are. In each moment, our sense of self is the brain's best statistical guess about our current identity and lived experience. This framework offers new ways to think about selfhood-not as fixed, but as adaptive and responsive.