Work

Signatures of infinity: Nonergodicity and resource scaling in prediction, complexity, and learning

Year: 2015

Type: article

Abstract: We introduce a simple analysis of the structural complexity of infinite-memory processes built from random samples of stationary, ergodic finite-memory component processes. Such processes are familiar from the well known multiarm Bandit problem. We contrast our analysis with computation-theoretic and statistical inference approaches to understanding their complexity. The result is an alternative view of the relationship between predictability, complexity, and learning that highlights the distinct ways in which informational and correlational divergences arise in complex ergodic and nonergodic processes. We draw out consequences for the resource divergences that delineate the structural hierarchy of ergodic processes and for processes that are themselves hierarchical.

Source: Physical Review E

DOI: 10.1103/physreve.91.050106

Authors: James P. Crutchfield, Sarah Marzen

Institutions: University of California, Davis, University of California, Berkeley

Language: English

Topic: Computability, Logic, AI Algorithms

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

Open Access status: green