Generation of human computational models with machine learning

Campuzano, Francisco and García-Valverde, Teresa and Botia Blaya, Juan A. and Serrano Fernández, Emilio (2015). Generation of human computational models with machine learning. "Information Sciences", v. 293 (n. 1); pp. 97-114. ISSN 0020-0255. https://doi.org/10.1016/j.ins.2014.09.008.

Description

Title: Generation of human computational models with machine learning
Author/s:
  • Campuzano, Francisco
  • García-Valverde, Teresa
  • Botia Blaya, Juan A.
  • Serrano Fernández, Emilio
Item Type: Article
Título de Revista/Publicación: Information Sciences
Date: February 2015
ISSN: 0020-0255
Volume: 293
Subjects:
Freetext Keywords: Smart environments testing; Human behavior modeling; Machine learning; Social simulation
Faculty: E.T.S. de Ingenieros Informáticos (UPM)
Department: Inteligencia Artificial
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Services in smart environments pursue to increase the quality of people?s lives. The most important issues when developing this kind of environments is testing and validating such services. These tasks usually imply high costs and annoying or unfeasible real-world testing. In such cases, artificial societies may be used to simulate the smart environment (i.e. physical environment, equipment and humans). With this aim, the CHROMUBE methodology guides test engineers when modeling human beings. Such models reproduce behaviors which are highly similar to the real ones. Originally, these models are based on automata whose transitions are governed by random variables. Automaton?s structure and the probability distribution functions of each random variable are determined by a manual test and error process. In this paper, it is presented an alternative extension of this methodology which avoids the said manual process. It is based on learning human behavior patterns automatically from sensor data by using machine learning techniques. The presented approach has been tested on a real scenario, where this extension has given highly accurate human behavior models,

Funding Projects

TypeCodeAcronymLeaderTitle
Government of SpainTEC2012-32457CALISTAUnspecifiedUnspecified

More information

Item ID: 35704
DC Identifier: http://oa.upm.es/35704/
OAI Identifier: oai:oa.upm.es:35704
DOI: 10.1016/j.ins.2014.09.008
Official URL: http://www.sciencedirect.com/science/article/pii/S0020025514009049
Deposited by: Memoria Investigacion
Deposited on: 08 Jul 2015 07:10
Last Modified: 31 May 2019 13:31
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