Acceptance of robotic systems will depend on how similar they are to human beings. It has been a long-standing open question how higher cognition, as necessary, e.g., for ethical decision making, could be built upon a low-level cognitive architecture. The Activation Bit Vector Machine (ABVM) is a novel cognitive architecture built upon Kanerva's Vector Symbolic Architecture abstraction for associative memory and backed by Zadeh's idea of "Computing with Words" and the formal logic theory of Fuzzy Logics that evolved from it. The ABVM architecture consists formally of a nested hierarchy of formal languages that is practically implemented through a nested architecture of theorem provers for these languages. The nesting of languages/provers was designed to allow reasoning complexity and thus reaction times and expressiveness to correspond to the demands of interactions with the real-world for the specific tasks covered. Originally designed to allow intelligent pervasive computing applications, partial implementations where applied in scenarios from printed electronics and industrial automation to business process monitoring. More importantly, however, it was recently discovered (published in late 2018) that the low-level implementation also presents a bi-directional connection-pathway not only from perception to logic but also backwards from logic to perception enabling a wealth of novel applications and further foundational research. A first application of this, the TextMap general purpose visualization system (in press), a tool that with a minimal ontology produces images from texts, presents a first demonstration of this potential.
A cognitive system for modeling foundations of higher cognition
VeranstaltungsortRaum A 1.03, Robert-Hooke-Str. 1 in Bremen
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