Neighborhood Selection and Rules Identification for Cellular Automata: A Rough Sets Approach

Autor:	Placzek, Bartlomiej
Rok vydání:	2014
Předmět:	Computer Science - Artificial Intelligence Nonlinear Sciences - Cellular Automata and Lattice Gases
Zdroj:	Lecture Notes in Computer Science, vol. 8385, pp. 721-730 (2014)
Druh dokumentu:	Working Paper
DOI:	10.1007/978-3-642-55195-6_68
Popis:	In this paper a method is proposed which uses data mining techniques based on rough sets theory to select neighborhood and determine update rule for cellular automata (CA). According to the proposed approach, neighborhood is detected by reducts calculations and a rule-learning algorithm is applied to induce a set of decision rules that define the evolution of CA. Experiments were performed with use of synthetic as well as real-world data sets. The results show that the introduced method allows identification of both deterministic and probabilistic CA-based models of real-world phenomena. Comment: 11 pages, 3 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1409.6359 Zobrazit plný text záznamu View this record from Arxiv