We present an axiomatic approach to meaninglessness in nite and transsnite term rewriting and lambda calculus. We justify our axioms in two ways. First, they are shown to imply important properties of mean-inglessness: genericity of the class of meaningless terms, the consistency of equating all meaningless terms, and the construction of BB ohm trees. Second we show that they can be easily veri...

There is ample evidence that the brain generates predictions that help interpret sensory input. To build such predictions the brain capitalizes upon learned statistical regularities and associations (e.g., "A" is followed by "B"; "C" appears together with "D"). The centrality of predictions to mental activities gave rise to the hypothesis that associative information with predictive value is pe...

Hierarchies, such as the tree of shapes, are popular representations for image simplification and segmentation thanks to their multiscale structures. Selecting meaningful level lines (boundaries of shapes) yields to simplify image while preserving intact salient structures. Many image simplification and segmentation methods are driven by the optimization of an energy functional, for instance th...

There has been much discussion recently about the scope and limits of purely symbolic models of the mind and abotlt the proper role of connectionism in cognitive modeling. This paper describes the "symbol grounding problem": How can the semantic interpretation of a formal symbol system be made intrinsic to the system, rather than just parasitic on the meanings in our heads? How can the meanings...