Giovanni Pezzulo

TL;DR: A cognitive phenomenon is obtained which generates a trace which is denoted as Electroexpectogram (EXG) which shows a learning process represented by the learned anticipation in the CNV anticipatory potential.

TL;DR: A novel perspective is offered that casts control and motivational processes as complementary aspects of active inference and hierarchical goal processing under deep generative models and proposes that the control hierarchy propagates prior preferences or goals, but their precision is informed by the motivational context.

TL;DR: Six authors from varying backgrounds and approaches address issues concerning the construction of embodied computational models, and illustrate what they view as the critical current and next steps toward mechanistic theories of embodiment.

TL;DR: This work offers a proof of principle that self-assembly is an emergent property of cells that share a common (genetic and epigenetic) model of organismal form and suggests an interpretation of genetic codes as parametrizing a generative model—predicting the signals sensed by cells in the target morphology—and epigenetic processes as the subsequent inversion of that model.

TL;DR: Results obtained at the SENSEVAL-2 initiative confirm that for a significant subset of words domain information can be used to disambiguate with a very high level of precision.