arXiv subjects

Robert Prentner

Publications and source records attributed to Robert Prentner.

8 recordsLinked to original sources

arXiv2026

Categorical AI phenomenology: A first-person approach

This paper develops a phenomenology-first approach to artificial consciousness by reframing consciousness as the subjective experience enacted through an agent's interface with the world. We shift the methodological focus to first-person structures, modeled mathematically by categories derived from Q-networks to capture actions and phenomenological invariants. In this framework, Q-networks are conceptualized as relational interfaces encoding agent-world interaction, analogous to how the dynamical states of a computer depend on its sensory inputs, previous states, and actions. Our work provides a rigorous framework for interface consciousness to describe computational systems that embed information-processing into phenomenological structure. The approach aligns with 4E approaches to cognition by emphasizing enactive, embedded, and extended dimensions of experience. The paper thus offers a principled, relational, and phenomenological account of artificial phenomenology grounded in categorical mathematics.

cs.AI↗

arXiv2025

Epistemoverse: Toward an AI-Driven Knowledge Metaverse for Intellectual Heritage Preservation

Large language models (LLMs) have often been characterized as "stochastic parrots" that merely reproduce fragments of their training data. This study challenges that assumption by demonstrating that, when placed in an appropriate dialogical context, LLMs can develop emergent conceptual structures and exhibit interaction-driven (re-)structuring of cognitive interfaces and reflective question-asking. Drawing on the biological principle of cloning and Socrates' maieutic method, we analyze authentic philosophical debates generated among AI-reincarnated philosophers within the interactive art installations of the Syntropic Counterpoints project. By engaging digital counterparts of Aristotle, Nietzsche, Machiavelli, and Sun Tzu in iterative discourse, the study reveals how machine dialogue can give rise to inferential coherence, reflective questioning, and creative synthesis. Based on these findings, we propose the concept of the Epistemoverse--a metaverse of knowledge where human and machine cognition intersect to preserve, reinterpret, and extend intellectual heritage through AI-driven interaction. This framework positions virtual and immersive environments as new spaces for epistemic exchange, digital heritage, and collaborative creativity.

cs.HC↗

arXiv2025

Artificial Consciousness as Interface Representation

Whether artificial intelligence (AI) systems can possess consciousness is a contentious question because of the inherent challenges of defining and operationalizing subjective experience. This paper proposes a framework to reframe the question of artificial consciousness into empirically tractable tests. We introduce three evaluative criteria - S (subjective-linguistic), L (latent-emergent), and P (phenomenological-structural) - collectively termed SLP-tests, which assess whether an AI system instantiates interface representations that facilitate consciousness-like properties. Drawing on category theory, we model interface representations as mappings between relational substrates (RS) and observable behaviors, akin to specific types of abstraction layers. The SLP-tests collectively operationalize subjective experience not as an intrinsic property of physical systems but as a functional interface to a relational entity.

cs.AI↗

arXiv2023

Measuring the integrated information of a quantum mechanism

Originally conceived as a theory of consciousness, integrated information theory (IIT) provides a theoretical framework intended to characterize the compositional causal information that a system, in its current state, specifies about itself. However, it remains to be determined whether IIT as a theory of consciousness is compatible with quantum mechanics as a theory of microphysics. Here, we present an extension of IIT's latest formalism to evaluate the mechanism integrated information ($φ$) of a system subset to finite-dimensional quantum systems (e.g., quantum logic gates). To that end, we translate a recently developed, unique measure of intrinsic information into a density matrix formulation, and extend the notion of conditional independence to accommodate quantum entanglement. The compositional nature of the IIT analysis might shed some light on the internal structure of composite quantum states and operators that cannot be obtained using standard information-theoretical analysis. Finally, our results should inform theoretical arguments about the link between consciousness, causation, and physics from the classical to the quantum.

quant-ph↗

arXiv2021

Pluralist-Monism. Derived Category Theory as the Grammar of n-Awareness

In this paper, we develop a mathematical model of awareness based on the idea of plurality. Instead of positing a singular principle, telos, or essence as noumenon, we model it as plurality accessible through multiple forms of awareness ("n-awareness"). In contrast to many other approaches, our model is committed to pluralist thinking. The noumenon is plural, and reality is neither reducible nor irreducible. Nothing dies out in meaning making. We begin by mathematizing the concept of awareness by appealing to the mathematical formalism of higher category theory. The beauty of higher category theory lies in its universality. Pluralism is categorical. In particular, we model awareness using the theories of derived categories and $(\infty, 1)$-topoi which will give rise to our meta-language. We then posit a "grammar" ("n-declension") which could express n-awareness, accompanied by a new temporal ontology ("n-time"). Our framework allows us to revisit old problems in the philosophy of time: how is change possible and what do we mean by simultaneity and coincidence? Another question which could be re-conceptualized in our model is one of soteriology related to this pluralism: what is a self in this context? A new model of "personal identity over time" is thus introduced.

math.GM↗

arXiv2021

Perfectoid Diamonds and n-Awareness. A Meta-Model of Subjective Experience

In this paper, we propose a mathematical model of subjective experience in terms of classes of hierarchical geometries of representations ("n-awareness"). We first outline a general framework by recalling concepts from higher category theory, homotopy theory, and the theory of (infinity, 1)-topoi. We then state three conjectures that enrich this framework. We first propose that the (infinity, 1)-category of a geometric structure known as perfectoid diamond is an (infinity, 1)-topos. In order to construct a topology on the (infinity, 1)-category of diamonds we then propose that topological localization, in the sense of Grothendieck-Rezk-Lurie (infinity, 1)-topoi, extends to the (infinity, 1)-category of diamonds. We provide a small-scale model using triangulated categories. Finally, our meta-model takes the form of Efimov K-theory of the (infinity, 1)-category of perfectoid diamonds, which illustrates structural equivalences between the category of diamonds and subjective experience (i.e. its privacy, self-containedness, and self-reflexivity). Based on this, we investigate implications of the model. We posit a grammar ("n-declension") for a novel language to express n-awareness, accompanied by a new temporal scheme ("n-time"). Our framework allows us to revisit old problems in the philosophy of time: how is change possible and what do we mean by simultaneity and coincidence? We also examine the notion of "self" within our framework. A new model of personal identity is introduced which resembles a categorical version of the "bundle theory"; selves are not substances in which properties inhere but (weakly) persistent moduli spaces in the K-theory of perfectoid diamonds.

math.GM↗

arXiv2020

Attracting Sets in Perceptual Networks

This document gives a specification for the model used in [1]. It presents a simple way of optimizing mutual information between some input and the attractors of a (noisy) network, using a genetic algorithm. The nodes of this network are modeled as simplified versions of the structures described in the "interface theory of perception" [2]. Accordingly, the system is referred to as a "perceptual network". The present paper is an edited version of technical parts of [1] and serves as accompanying text for the Python implementation PerceptualNetworks, freely available under [3]. 1. Prentner, R., and Fields, C.. Using AI methods to Evaluate a Minimal Model for Perception. OpenPhilosophy 2019, 2, 503-524. 2. Hoffman, D. D., Prakash, C., and Singh, M.. The Interface Theory of Perception. Psychonomic Bulletin and Review 2015, 22, 1480-1506. 3. Prentner, R.. PerceptualNetworks. https://github.com/RobertPrentner/PerceptualNetworks. (accessed September 17 2020)

q-bio.NC↗

arXiv2020

A Predictive Strategy for the Iterated Prisoner's Dilemma

The iterated prisoner's dilemma is a game that produces many counter-intuitive and complex behaviors in a social environment, based on very simple basic rules. It illustrates that cooperation can be a good thing even in a competitive world, that individual fitness needs not to be the most important criteria of success, and that some strategies are very strong in a direct confrontation but could still perform poorly on average or are evolutionarily unstable. In this contribution, we present a strategy -- PREDICTOR -- which appears to be "sentient" and chooses to cooperate when playing against some strategies, but defects when playing against others, without the need to record "tags" for its opponents or an involved decision-making mechanism. To be able to operate in the highly-contextual environment, as modeled by the iterated prisoner's dilemma, PREDICTOR learns from its experience to choose optimal actions by modeling its opponent and predicting a (fictive) future. It is shown that PREDICTOR is an efficient strategy for playing the iterated prisoner's dilemma and is simple to implement. In a simulated and representative tournament, it achieves high average scores and wins the tournament for various parameter settings. PREDICTOR thereby relies on a brief phase of exploration to improve its model, and it can evolve morality from intrinsically selfish behavior.

cs.GT↗