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Formas persistentes: de Pitágoras a la Teoría de Kolmogorov

Giulio Ruffini

P4·Philosophy & EthicsL1·Philosophy
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This work presents a structured theoretical framework for understanding mind, agency, and experience through the lens of algorithmic information theory, tracing a philosophical lineage from Pythagoras and Aristotle through Kant and Turing to Kolmogorov. The framework, designated KT-ESP, proposes that an agent can be modeled as an algorithmic entity that receives information, constructs compressed internal representations analogous to ZIP compression, and acts in accordance with structured experiential valence. Drawing on Shannon's information theory, Kolmogorov complexity, Church-Turing computability, and Wolpert's thermodynamic limits of computation, the work argues that genuine mental content and structured experience are amenable to formal, computable description. The scope is primarily theoretical and position-oriented, synthesizing philosophy of mind, computational theory, and cognitive science into a unified account of the algorithmic agent. A concluding section extends the framework toward the quantification of qualia, suggesting that subjective experiential qualities need not remain beyond the reach of rigorous formalization.

A slide deck arguing that minds, agency, and even subjective experience can be given rigorous algorithmic descriptions — no hand-waving required.

This is a 20-minute talk (in Spanish), not a full paper. The source is a Beamer slide-deck scaffold: it's mostly LaTeX plumbing that assembles pre-existing slide images into a structured presentation. The actual argumentative content lives in those embedded image files, which are not included here. So this summary is necessarily limited to what the structure and slide titles reveal.

The central bet is that an agent — any agent, including a conscious one — can be modeled as an algorithm that receives data, compresses it into an internal model (the talk literally uses a ZIP file as the analogy), and then acts based on that compressed representation. The compression framing is doing real work: Kolmogorov complexity, the information-theoretic measure of how compressible a string is, becomes the formal backbone for what it means to "understand" something. Shannon entropy handles the statistical side; Kolmogorov complexity handles the deeper, program-length side.

The philosophical lineage the talk traces — Pythagoras → Aristotle → Kant → Turing → Kolmogorov — is meant to show this isn't a bolt-from-the-blue computational claim but the latest step in a long tradition of arguing that structure, not substance, is what matters for mind. Aristotle's hylomorphism (the idea that form, not matter, defines a thing) and Kant's notion that the mind actively structures experience both get recruited as ancestors of the KT-ESP framework. Wolpert's thermodynamic limits on computation and the Church-Turing thesis are brought in to bound what's actually computable, keeping the framework honest about its scope.

The most ambitious move comes at the end: the talk claims that qualia — the raw "what it's like" of experience, traditionally considered the hard problem's hardest part — can begin to be quantified within this framework. The slide title says "we begin to quantify qualia," which is a strong claim. The source does not make explicit how that quantification works mechanically; that detail presumably lives in the slide images themselves or in companion papers.

Zenodo
10.5281/zenodo.21326169
WP ID
WP0201
Lifecycle
completed
Visibility
public
Access level
open
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Priority
Collab
closed
Venue
DOI
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Source
drive_legacy
Repo path
WP0201
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