An Enactivist-Inspired Mathematical Model of Cognition
Vadim Weinstein, Basak Sakcak, Steven M. LaValle

TL;DR
This paper develops a mathematical framework for cognition inspired by enactivist principles, emphasizing the inseparability of agents and environment, and avoiding symbolic representations, to bridge philosophy and computational modeling.
Contribution
It introduces a formal mathematical model of enactivist cognition, including the concept of sufficiency and related notions, aligning cognitive systems with enactivist tenets.
Findings
Proves a uniqueness theorem for minimal sufficient refinements
Shows sufficiency aligns with known information spaces
Develops hierarchical and strategic notions of sufficiency
Abstract
We formulate five basic tenets of enactivist cognitive science that we have carefully identified in the relevant literature as the main underlying principles of that philosophy. We then develop a mathematical framework to talk about cognitive systems (both artificial and natural) which complies with these enactivist tenets. In particular we pay attention that our mathematical modeling does not attribute contentful symbolic representations to the agents, and that the agent's brain, body and environment are modeled in a way that makes them an inseparable part of a greater totality. The purpose is to create a mathematical foundation for cognition which is in line with enactivism. We see two main benefits of doing so: (1) It enables enactivist ideas to be more accessible for computer scientists, AI researchers, roboticists, cognitive scientists, and psychologists, and (2) it gives the…
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Taxonomy
TopicsComputability, Logic, AI Algorithms · Logic, Reasoning, and Knowledge · Embodied and Extended Cognition
