2000/01/29 by Cosma Rohilla Shalizi, James P. Crutchfield, Shalizi, Cosma Rohilla +1
Computer Science · #Computability, Logic, AI Algorithms #Evolutionary Algorithms and Applications #F.1.3 #FOS: Computer and information sciences #G.3 #H.1.1 #I.2.6 #Machine Learning (cs.LG) #Neural Networks and Applications #Neural and Evolutionary Computing (cs.NE) #cs.LG #cs.NE
paper · pdf · doi:10.48550/arxiv.cs/0001027
12 pages, 3 figures; submitted to the Proceedings of the 17th International Conference on Machine Learning (differs slightly in pagination and citation format from that version)
arxiv created 2000/01/29 · openalex publication_date 2000/01/29 · arxiv updated 2009/11/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Computational mechanics is a method for discovering, describing and quantifying patterns, using tools from statistical physics. It constructs optimal, minimal models of stochastic processes and their underlying causal structures. These models tell us about the intrinsic computation embedded within a process---how it stores and transforms information. Here we summarize the mathematics of computational mechanics, especially recent optimality and uniqueness results. We also expound the principles and motivations underlying computational mechanics, emphasizing its connections to the minimum description length principle, PAC theory, and other aspects of machine learning.