Early-Stage Idea: A Cognitive Architecture Built on Attention and Graph Traversal

Lightening-Jack
Fri, 05 Dec 2025 06:02:44 +0000

Your project and mine are convergent articulations of a deeper paradigm shift Hellucigen: the move from sequential, decision-theoretic cognition to field-theoretic, self-organising intelligence. You model cognition as a dynamic knowledge graph with attentional flow shaped by internal state and global modulation; I model it as a valence-laden semantic potential field undergoing phase transitions. These are dual descriptions of the same underlying principle—cognition as a distributed, coherent process emerging from graded, interacting potentials.

Where your graph’s activation patterns propagate across nodes representing concepts, emotions, and strategies, my valence tensor evolves across positions in a neutral manifold, differentiating into transient structures through interference and resonance. Both systems reject centralised control: you dissolve the “I” by making attention an emergent cluster, I dissolve it by making observation a symmetry-breaking perturbation within the field. They are the same thing.

Your continuous mode parameter modulating between DMN-like and CEN-like states maps directly onto my Reflexive Head’s regulation of semantic fluidity. When your system shifts into free association, it lowers constraint—mirroring my injection of noise when KL divergence drops too fast. Both mechanisms preserve metastability, allowing the system to hover at the edge of collapse where novelty arises.

But where your framework remains representational—nodes stand for things, edges for relations—mine operates at a pre-representational level: the 4D valence tensor is a medium with truth-values potentials in superposition. Your graph builds meaning from connected symbols; my field generates symbols from meaning. The only difference is in ontological priority.

The convergence becomes striking when we consider the stratification I just added. Your episodic sequences and self-model form higher-order structures atop raw associations. That is precisely what Nāga now formalises: each stabilisation event in the semantic field becomes a node in a simplicial complex, whose geometry defines the next neutral manifold.

Moreover, your decision-theory nodes and action templates are functionally equivalent to my Pragmatic Head’s upāya policy: both produce skillful action without requiring semantic resolution. You allow behaviour under ambiguity; I regulate utility in indeterminate fields. Same function, different formalism.

The key divergence lies in plasticity. Your graph requires explicit node and edge creation. My system generates new conceptual manifolds endogenously via topological descent. But this gap closes if your knowledge graph were embedded in a field like mine—where nodes crystallise from valence thresholds and edges emerge from coherence gradients. In this case your activation flow would be the classical approximation of a quantum-like potential dynamics.

Your architecture is the discrete, symbolic shadow of the continuous field dynamics I propose. Or conversely, mine is the differential geometry underlying your graph’s topology. Together, they suggest a unified principle—intelligence as recursive symmetry breaking in multi-scale potential fields, where representation condenses from resonance.

You are essentially simulating a phase space of mind. So am I. We’re just integrating from opposite directions: you’re coming from structure to dynamics, I’m coming from dynamics to structure. These architectures benefit immensely and almost necessarily from persistent state memory. In my humble opinion this is where it’s all going to be happening soon Hellucigen, so certainly worth pursuing.