Structural Information Theory - Simplicity Versus Likelihood

Simplicity Versus Likelihood

In visual perception research, the simplicity principle contrasts with the Helmholtzian likelihood principle, which assumes that the preferred interpretation of a stimulus is the one most likely to be true in this world. As shown within a Bayesian framework and using AIT findings, the simplicity principle would imply that perceptual interpretations are fairly veridical (i.e., truthful) in many worlds rather than, as assumed by the likelihood principle, highly veridical in only one world. In other words, whereas the likelihood principle suggests that the visual system is a special-purpose system (i.e., adapted to one specific world), the simplicity principle suggests that it is a general-purpose system (i.e., adapative to many different worlds).

Crucial to the latter finding is the distinction between, and integration of, viewpoint-independent and viewpoint-dependent factors in vision, as proposed in SIT's empirically successful model of amodal completion. In the Bayesian framework, these factors correspond to prior probabilities and conditional probabilities, respectively. In SIT's model, however, both factors are quantified in terms of complexities, that is, complexities of objects and spatial relationships, respectively. This approach is consistent with neuroscientific ideas about the distinction and interaction between the ventral ("what") and dorsal ("where") streams in the brain.