Time-consciousness in computational phenomenology: a temporal analysis of active inference

Time is central to both science and daily life, yet computational models of consciousness usually treat time as a sequence, not a continuous flow. This creates a problem for computational phenomenology, which combines phenomenology with computational modeling. By analyzing the active inference framework's temporal structure, the authors show that an integrated continuity of time can be achieved by merging Husserlian temporality with sequential time. A Markov blanket of the present moment integrates past and future moments of both subjective temporality and objective time asynchronously. The authors conclude that active inference qualifies as a computational model for phenomenological investigations regarding time.

Study at a glance

Abstract

Abstract Time plays a significant role in science and everyday life. Despite being experienced as a continuous flow, computational models of consciousness are typically restricted to a sequential temporal structure. This difference poses a serious challenge for computational phenomenology—a novel field combining phenomenology and computational modelling. By analysing the temporal structure of the active inference framework, we show that an integrated continuity of time can be achieved by merging Husserlian temporality with a sequential order of time. We also show that a Markov blanket of the present moment integrates past and future moments of both subjective temporality and objective time in an asynchronous manner. By applying the integrated continuity, it is clear that active inference makes use of both subjective temporality and objective time in an integrated fashion. We conclude that active inference, on a temporal note, qualifies as a computational model for phenomenological investigations.