Derives Boltzmann distributions for 1D spin models as stochastic processes, quantifies structure via excess entropy and statistical complexity, specifies mechanisms with epsilon-machines, and reports agreement with typical configurations.
Crutchfield
7 Pith papers cite this work. Polarity classification is still indexing.
7
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
years
2026 7roles
background 1polarities
background 1representative citing papers
Canonical functionalism identifies consciousness-relevant functional organization with the minimal state-transition structure obtained by equating internal states that exhibit identical future behavior under all possible continuations.
A constructor theory framework models prebiotic information as physical differences and meaning as functional consequences in Casimir-Lifshitz protocell clusters.
Casimir-stabilized protocell clusters form ε-machines whose attractor states and transitions create emergent prebiotic information through physical memory rather than molecular polymers.
Introduces a defeasible rule-based coaching layer that converts diagnostic failures into policy rule revisions in adaptive agent-based regulatory simulations, demonstrated on an emissions-regulation ABM.
Neural network learning opacity stems from three dynamical complexity properties in training, rendering some sources of opacity irreducible.
citing papers explorer
-
What Is a Pattern in Statistical Mechanics? Formalizing Structure and Patterns in One-Dimensional Spin Lattice Models with Computational Mechanics
Derives Boltzmann distributions for 1D spin models as stochastic processes, quantifies structure via excess entropy and statistical complexity, specifies mechanisms with epsilon-machines, and reports agreement with typical configurations.