A Causal MultiAgent System Approach for Automating Processes in Intelligent Organizations

Hdl Handle:
http://hdl.handle.net/11285/572536
Title:
A Causal MultiAgent System Approach for Automating Processes in Intelligent Organizations
Issue Date:
2010-12-01
Abstract:
The current competitive environment motivated Knowledge Management (KM) theorists to propose the notion of Organizational Intelligence (OI) for enabling a rapid response of large organizations to changing conditions. KM practitioners consider that OI resides in both processes and members of the organization, and recommend implementing learning mechanisms and empowering participants with knowledge and decision making for improving organization competitiveness. In that sense, have being provided some theoretical definitions and practical approaches (e.g. Electronic Institutions and Autonomic Computing), as well as commercial platforms (e.g. Whitestein Technologies), that implement OI to a certain extent. Some of these approaches have already taken advantage of tools and formalisms developed in Artificial Intelligence (e.g. Knowledge Representation, Data Mining, and Intelligent Agents). In this research, I propose the use of Aristotelian Causality for modeling organizations, as well as its members, as intelligent entities through the Causal Artificial Intelligence Design (CAID) theory, and present the Causal Multi-Agent System (CMAS) framework for automating organizational processes. Bayesian Causal Networks are extended to Semantic Causal Networks (SCN) for providing an explicit representation of the goals, participants, resources and knowledge involved in these processes. The CAID principles and the SCN formalism are used for providing a probabilistic extension of the goal-driven Belief-Desire-Intention agent architecture, called Causal Agent. Lastly, the capabilities of this framework are demonstrated through the specification and automation of an information auditing process.
Keywords:
Philosophical; Metaphysics; Nonmonotonic
Degree Program:
Doctoral Program in Inforation Technologies and Commuications
Advisors:
Dr. Francisco J. CantÚ Ortíz
Committee Member / Sinodal:
Dr. Ramón F. Brena Pinero; Dr. Antonio Sánchez Aguilar; Dr. Pablo Noriega; Dr. Leonardo Garrido
Degree Level:
Doctor of Philosophy in Information Technologies and Communications
School:
Division Of Mechatronics And Information Technologies
Campus Program:
Campus Monterrey
Discipline:
Ingeniería y Ciencias Aplicadas / Engineering & Applied Sciences
Appears in Collections:
Ciencias Exactas

Full metadata record

DC FieldValue Language
dc.contributor.advisorDr. Francisco J. CantÚ Ortízes
dc.creatorHector G. Ceballosen
dc.date.accessioned2015-08-17T11:34:42Zen
dc.date.available2015-08-17T11:34:42Zen
dc.date.issued2010-12-01-
dc.identifier.urihttp://hdl.handle.net/11285/572536en
dc.description.abstractThe current competitive environment motivated Knowledge Management (KM) theorists to propose the notion of Organizational Intelligence (OI) for enabling a rapid response of large organizations to changing conditions. KM practitioners consider that OI resides in both processes and members of the organization, and recommend implementing learning mechanisms and empowering participants with knowledge and decision making for improving organization competitiveness. In that sense, have being provided some theoretical definitions and practical approaches (e.g. Electronic Institutions and Autonomic Computing), as well as commercial platforms (e.g. Whitestein Technologies), that implement OI to a certain extent. Some of these approaches have already taken advantage of tools and formalisms developed in Artificial Intelligence (e.g. Knowledge Representation, Data Mining, and Intelligent Agents). In this research, I propose the use of Aristotelian Causality for modeling organizations, as well as its members, as intelligent entities through the Causal Artificial Intelligence Design (CAID) theory, and present the Causal Multi-Agent System (CMAS) framework for automating organizational processes. Bayesian Causal Networks are extended to Semantic Causal Networks (SCN) for providing an explicit representation of the goals, participants, resources and knowledge involved in these processes. The CAID principles and the SCN formalism are used for providing a probabilistic extension of the goal-driven Belief-Desire-Intention agent architecture, called Causal Agent. Lastly, the capabilities of this framework are demonstrated through the specification and automation of an information auditing process.en
dc.language.isoenen
dc.rightsOpen Accessen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.titleA Causal MultiAgent System Approach for Automating Processes in Intelligent Organizationsen
dc.typeTesis de Doctoradoes
thesis.degree.grantorInstituto Tecnológico y de Estudios Superiores de Monterreyes
thesis.degree.levelDoctor of Philosophy in Information Technologies and Communicationsen
dc.contributor.committeememberDr. Ramón F. Brena Pineroes
dc.contributor.committeememberDr. Antonio Sánchez Aguilares
dc.contributor.committeememberDr. Pablo Noriegaes
dc.contributor.committeememberDr. Leonardo Garridoes
thesis.degree.disciplineDivision Of Mechatronics And Information Technologiesen
thesis.degree.nameDoctoral Program in Inforation Technologies and Commuicationsen
dc.subject.keywordPhilosophicalen
dc.subject.keywordMetaphysicsen
dc.subject.keywordNonmonotonicen
thesis.degree.programCampus Monterreyes
dc.subject.disciplineIngeniería y Ciencias Aplicadas / Engineering & Applied Scienceses
All Items in REPOSITORIO DEL TECNOLOGICO DE MONTERREY are protected by copyright, with all rights reserved, unless otherwise indicated.