James P. Crutchfield

TL;DR: A recent synchronization analysis of exact finite-state sources to nonexact sources for which synchronization occurs only asymptotically is extended and it is found that an observer’s average uncertainty in the source state vanishes exponentially fast and, as a consequence, an observer'saverage uncertainty in predicting future output converges exponentially fast to the source entropy rate.

TL;DR: A direct and complete analysis of intrinsic computation is now available for the temporal organization of finitary hidden Markov models and nonlinear dynamical systems with generating partitions and for the spatial organization in one-dimensional systems, including spin systems, cellular automata, and complex materials via chaotic crystallography.

TL;DR: It is shown that the total uncertainty experienced by the agent during the process is closely related to the transient information, a new quantity that captures the manner in which the environment's entropy growth curve converges to its asymptotic form.

TL;DR: Evidence is found that the excess entropy and regularized statistical complexity of different types of integrate-and-fire neurons are universal in the continuous-time limit in the sense that they do not depend on mechanism details, suggesting a surprising simplicity in the spike trains generated by these model neurons.

TL;DR: In this paper, the authors introduce stochastic and quantum finite-state transducers as computation-theoretic models of quantum finitary processes and compare deterministic and non-deterministic versions, summarizing their relative computational power.