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Gualtiero Piccinini

Publications and source records attributed to Gualtiero Piccinini.

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Allocentric Navigation Is Computationally Universal

This report presents three proofs showing that idealized architectures capable of navigation guided by allocentric maps with landmark structure can be computationally universal. The navigation may occur either online (in the environment) or offline (in the animal's head). The first proof proceeds from a universal two-counter machine by encoding counters as the positions of two movable markers on orthogonal coordinate axes. The second proof directly simulates an ordinary one-tape Turing machine by using a writable tape-path embedded in the map. The third proof strengthens locality by replacing the globally designated path with a two-dimensional field of landmarks that carries only local predecessor/successor information. These constructions are mathematically close to classical graph-based models in computability theory, including Kolmogorov-Uspensky machines, storage-modification machines, graph Turing machines, and related navigation-on-graphs models. Accordingly, the bare universality results are mathematically unsurprising. Nevertheless, the present treatment is, as far as I know, the first self-contained reconstruction of such universality demonstrations in the idiom of allocentric cognitive maps and offline navigation, that is, within an architecture whose core representational and computational primitives are drawn from a body of empirical and theoretical work on spatial navigation. The report therefore reframes known computability-theoretic ideas to show that an allocentric navigation-based architecture can be computationally universal.

q-bio.NC

Neural Hardware for the Language of Thought: New Rules for an Old Game

The Language of Thought (LOT) hypothesis posits that at least some important cognitive processes involve language-like representations. These representations must be processed by appropriate hardware. Since the organ of biological cognition is the nervous system, whether biological cognition relies on a LOT depends on how neural hardware works. I distinguish between different versions of LOT, articulate their hardware requirements, and consider which versions of LOT are supported by empirical evidence. I argue that the Classical LOT hypothesis (Fodor 1975) is ruled out; the version of LOT that is best supported by empirical evidence is the Nonclassical LOT thesis that some neural representations mirror some of the structure of natural language and represent in a language-like way, yet they encode information nondigitally and are processed by ordinary (nondigital, and hence Nonclassical) neural computations that rely not only on syntactic structure but many other features.

q-bio.NC