Prototyping an intelligent decision support system for improving urban infrastructures management

This paper describes an intelligent decision support system (IDSS) dedicated to coordinated management of urban infrastructures (SIGIU). This system identifies the data and related treatments common to several municipal activities and defines the requirements and functionalities of the computer tools developed to improve the delivery, performance and coordination of municipal services to the population. The resulting cooperative system called SIGIU is composed of a global planning and coordination system (SYGEC) and a set of integrated operating systems (SYDEX), each of them being associated with a specific urban system (sewerage, waterworks, etc.). In order to support the decision-making process, an IDSS was developed as a knowledge-based system provided with inference mechanisms that enables SYGEC and SYDEX to make strategic choices in terms of technical interventions on municipal infrastructures. The knowledge-based system stores experts' knowledge as well as solutions to past problems. Preliminary implementation results show that SIGIU effectively and efficiently supports the decision-making process related to managing urban infrastructures.

[1]  Camille Rosenthal-Sabroux,et al.  Developing an “Intelligent” DSS for the multicriteria evaluation of railway timetables: problems and issues , 1996 .

[2]  Catholijn M. Jonker,et al.  An Electronic Market Place: Generic Agent Models, Ontologies and Knowledge. , 1999 .

[3]  Catholijn M. Jonker,et al.  Compositional design and reuse of a generic agent model , 2000, Appl. Artif. Intell..

[4]  Michael R. Genesereth,et al.  Knowledge Interchange Format , 1991, KR.

[5]  Jean-Charles Pomerol,et al.  Systèmes interactifs d'aide à la décision et systèmes experts , 1989 .

[6]  Edmund H. Durfee,et al.  Coordination as distributed search in a hierarchical behavior space , 1991, IEEE Trans. Syst. Man Cybern..

[7]  Ian D. Watson,et al.  Applying case-based reasoning - techniques for the enterprise systems , 1997 .

[8]  Patrick Brézillon,et al.  Lecture Notes in Artificial Intelligence , 1999 .

[9]  Eithan Ephrati,et al.  Multi-Agent Planning as a Dynamic Search for Social Consensus , 1993, IJCAI.

[10]  George P. Huber,et al.  A theory of the effects of advanced information technologies on organizational design, intelligence , 1990 .

[11]  Catholijn M. Jonker,et al.  Distributed Scheduling to Support a Call Center: A Cooperative Multiagent Approach , 1999, Appl. Artif. Intell..

[12]  Thomas R. Gruber,et al.  Toward principles for the design of ontologies used for knowledge sharing? , 1995, Int. J. Hum. Comput. Stud..

[13]  Catholijn M. Jonker,et al.  Deliberate Evolution in Multi-Agent Systems , 1998, AID.

[14]  Tim Finin,et al.  KQML - A Language and Protocol for Knowledge and Information Exchange , 1994 .

[15]  Peter B. Denyer,et al.  An intelligent alarm system , 1992 .

[16]  Randall Davis,et al.  Negotiation as a Metaphor for Distributed Problem Solving , 1988, Artif. Intell..

[17]  Nicholas R. Jennings,et al.  Coordination in software agent systems , 1996 .

[18]  Nicholas R. Jennings,et al.  Argumentation and Multi-Agent Decision Making , 1998, AAAI Conference on Artificial Intelligence.

[19]  Janet L. Kolodner,et al.  An introduction to case-based reasoning , 1992, Artificial Intelligence Review.

[20]  Michael Wooldridge A Knowledge-theoretic Approach to Distributed Problem Solving , 1998, ECAI.

[21]  Janet L. Kolodner,et al.  Case-Based Reasoning , 1988, IJCAI 1989.

[22]  Nicholas R. Jennings,et al.  Agent Theories, Architectures, and Languages: A Survey , 1995, ECAI Workshop on Agent Theories, Architectures, and Languages.

[23]  James R. McDonald,et al.  The use of artificial neural networks for condition monitoring of electrical power transformers , 1998, Neurocomputing.

[24]  Nicholas R. Jennings,et al.  Coordination techniques for distributed artificial intelligence , 1996 .

[25]  Timothy W. Finin,et al.  KQML as an agent communication language , 1994, CIKM '94.

[26]  T. Norman,et al.  FORMALISING COLLABORATIVE DECISION-MAKING AND PRACTICAL REASONING IN MULTI-AGENT SYSTEMS , 2001 .

[27]  J. Wyatt Decision support systems. , 2000, Journal of the Royal Society of Medicine.

[28]  Edmund H. Durfee,et al.  Trends in Cooperative Distributed Problem Solving , 1989, IEEE Trans. Knowl. Data Eng..

[29]  Danny B. Lange,et al.  Programming and Deploying Mobile Agents with Java Aglets , 1998 .

[30]  Nicholas R. Jennings,et al.  Foundations of distributed artificial intelligence , 1996, Sixth-generation computer technology series.

[31]  Kevin Warwick,et al.  Artificial intelligence techniques in power systems , 1997 .

[32]  Agnar Aamodt,et al.  Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches , 1994, AI Commun..

[33]  James R. McDonald,et al.  COMMAS (COndition Monitoring Multi-Agent System) , 2001, Autonomous Agents and Multi-Agent Systems.

[34]  Peter Ucko Some highlights of the 2002/2003 academic year , 2002 .

[35]  Danny B. Lange,et al.  Programming and Deploying Java¿ Mobile Agents with Aglets¿ , 1998 .

[36]  J. R. McDonald,et al.  Knowledge and model based decision support for power system protection engineers , 1996, Proceedings of International Conference on Intelligent System Application to Power Systems.

[37]  Efraim Turban,et al.  Decision support systems and intelligent systems , 1997 .

[38]  Nicholas R. Jennings,et al.  Formalizing Collaborative Decision-making and Practical Reasoning in Multi-agent Systems , 2002, J. Log. Comput..

[39]  A. Roadmapof A Roadmap of Agent Research and Development , 1995 .

[40]  Edmund H. Durfee,et al.  Rational Coordination in Multi-Agent Environments , 2000, Autonomous Agents and Multi-Agent Systems.

[41]  Danny B. Lange,et al.  Seven good reasons for mobile agents , 1999, CACM.

[42]  Michel R. Klein,et al.  Knowledge-based decision support systems , 1995 .