A model-based approach for development of multi-agent software systems



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VITA

NAME Haiping Xu


EDUCATION B.S., Electrical Engineering, Zhejiang University, Hangzhou, China, 1989
M.S., Electrical Engineering, Zhejiang University, Hangzhou, China, 1992
M.S., Computer Science, Wright State University, Dayton, Ohio, 1998
Ph.D., Computer Science, University of Illinois, Chicago, Illinois, 2003
WORK Concurrent Software Systems Laboratory,

EXPERIENCE University of Illinois at Chicago, Chicago, Illinois, 1998 – 2003


Parallel Computing Laboratory,

Wright State University, Dayton, Ohio, 1996 – 1998


Intelligent Systems Laboratory,

Nanyang Technological University, Singapore, 1996


Hewlett-Packard Company, Beijing, China, 1995 – 1996
Shen-Yan Systems Technology, Inc., Beijing, China, 1992 – 1995
TEACHING Department of Computer Science

EXPERIENCE University of Illinois at Chicago, Chicago, Illinois, 1999 – 2003


HONORS University Fellowship, University of Illinois, Chicago, Illinois, 2001
Dayton Area Graduate Studies Institute (DAGSI) Scholarship, Ohio, 1998
Excellent Graduate Student of Zhejiang University, China, 1992
Guang-Hua National Merit Scholarship, China, 1990
Graduate Scholarship of Zhejiang University, China, 1990
Zhejiang University Special Class for Gifted Young, China, 1985
PROFESSIONAL Member of IEEE, IEEE Computer Society, and IEEE SMC Society

MEMBERSHIP Member of Association for Computing Machinery (ACM)


REFEREE IEEE Transactions on Multimedia (IEEE TMM)

IEEE Transactions on Parallel and Distributed Systems (IEEE TPDS)

International Journal of Software Engineering & Knowledge Engineering (IJSEKE)

International Conference on Distributed Computing Systems (ICDCS)

International Conference on Application and Theory of Petri Nets (ICATPN)

International Symposium on Software Engineering for Parallel and Distributed Systems (PDSE)



PUBLICATIONS OF THE AUTHOR


  1. H. Xu and S. M. Shatz, “ADK: An Agent Development Kit Based on a Formal Model for Multi-Agent Systems,” Submitted to Automated Software Engineering, February 2003.

  2. H. Xu and S. M. Shatz, “A Framework for Model-Based Design of Agent-Oriented Software,” IEEE Transactions on Software Engineering (IEEE TSE), Vol. 29, No. 1, January 2003, pp. 15-30.

  3. H. Xu and S. M. Shatz, “A Framework for Modeling Agent-Oriented Software,” In Proceedings of the 21st International Conference on Distributed Computing Systems (ICDCS-21), April 2001, Phoenix, Arizona, USA, pp. 57-64.

  4. H. Xu and S. M. Shatz, “An Agent-Based Petri Net Model with Application to Seller/Buyer Design in Electronic Commerce,” In Proceedings of the Fifth International Symposium on Autonomous Decentralized Systems (ISADS 2001), March 2001, Dallas, Texas, USA, pp. 11-18.

  5. H. Xu and S. M. Shatz, “Extending G-Nets to Support Inheritance Modeling in Concurrent Object-Oriented Design,” In Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (SMC 2000), October 8-11, 2000, Nashville, Tennessee, USA, pp. 3128-3133.

  6. R. K. Gedela, S. M. Shatz and H. Xu, “Compositional Petri Net Models of Advanced Tasking in Ada-95,” Computer Languages, Vol. 25, No. 2, July 1999, pp. 55-87.

  7. R. K. Gedela, S. M. Shatz and H. Xu, “Formal Modeling of Synchronization Methods for Concurrent Objects in Ada 95,” In Proceedings of the ACM Annual International Conference on Ada (SIGAda'99), October 17-21, 1999, Redondo Beach, CA, USA, pp. 211-220.

  8. K. Warendorf, H. Xu, and A. Verhoeven, “Case-Based Instructional Planning for Learning in a Context,” In Proceedings of the Joint 1997 Pacific Asian Conference on Expert Systems / Singapore International Conference on Intelligent Systems (PACES/SPICIS 97), February 24-27, 1997, Singapore, pp. 354-360.

  9. H. Xu, The Basic Study and Partial Implementation of Intelligent Chinese Tutoring System, Masters Thesis, Zhejiang University, Hangzhou, China, January 1992.

  10. H. Xu, X. Ruan, Z. Chen, S. Hu and H. Ren, “ICTS: Hypertext and Multi-Knowledge Source Based Intelligent Chinese Tutoring System,” Journal of Chinese Information Processing, 1992, Vol. 6, No. 2, pp. 8-16.

  11. Q. Hu, H. Xu, Y. Zhang and C. Zhou, “Software Design of an Expert Control System in Vacuum Distillation,” Control and Instruments in Chemical Industry, 1992, Vol. 19, No. 4, pp. 25-29.

  12. H. Xu, Z. Chen, and S. Hu, “Design and Implementation Techniques for an Intelligent Chinese Tutoring System,” In Proceedings of the Second National Conference on Computer Application, October 1991, Beijing, China, pp. 988-991.

  13. X. Ruan, S. Hu, Z. Chen, and H. Xu, “The Presentation and Inference of Chinese Language Knowledge,” In Proceedings of the International Conference on Information & System, A.M.S.E., October 1991, Hangzhou, China.

  14. H. Xu, “Software Design of a Microcomputer-Based Nuclear Scaler,” Process Automation Instrumentation, 1991, Vol. 12, No. 10, pp. 13-16.

  15. X. Ruan, H. Xu, and Z. Chen, “Intelligent CAI and Chinese Tutoring System,” Communications of Computation and Information, June 1991, No. 7, pp. 6-14.

A MODEL-BASED APPROACH FOR DEVELOPMENT OF

MULTI-AGENT SOFTWARE SYSTEMS
Haiping Xu, Ph.D.

Department of Computer Science

University of Illinois at Chicago

Chicago, Illinois (2003)


The advent of multi-agent systems has brought opportunities for the development of complex software that will serve as the infrastructure for advanced distributed applications. During the past decade, there have been many agent architectures proposed for implementing agent-based systems, and also some efforts to formally specify agent behaviors. However, research on narrowing the gap between agent formal models and agent implementation is rare. In this thesis, we present a model-based approach to designing and implementing multi-agent software systems. Instead of using formal methods only for the purpose of specifying agent behavior, we bring formal methods into the design phase of the agent development life cycle. Our approach is based on the G-net formalism, which is a type of high-level Petri net defined to support modeling of a system as a set of independent and loosely-coupled modules.
We first introduce how to extend G-nets to support class modeling and inheritance modeling for concurrent object-oriented design. Then, by viewing an agent as an extension of an object with mental states, we derive an agent-oriented G-net model from our extended G-nets that support class modeling. The agent-oriented G-net model serves as a high-level design for intelligent agents in multi-agent systems. To illustrate our formal modeling technique for agent-oriented software, an example of an agent family in electronic commerce is provided. We show how an existing Petri net tool can be used to detect design errors, and how model checking techniques can support the verification of some key behavioral properties of our agent models. In addition, we adapt the agent-oriented G-net model to support basic mobility concepts, and present design models of intelligent mobile agents. Finally, based on the high-level design, we derive the agent architecture and the detailed design needed for agent implementation. To demonstrate the feasibility of our approach, we describe a toolkit called ADK (Agent Development Kit) that supports rapid development of application-specific agents for multi-agent systems.

1 We view the abstract of a set of similar agents as an agent class, and we call an instance of an agent class an agent or an agent object.

2 One of the limitations for invariant approach is that it is not sufficient to prove a Petri net is L4-live or live, i.e., from any marking M that is reachable from M0, it is possible to ultimately fire any transition of the net.


3 Actually, this module purposely contains a somewhat subtle design error that is used to demonstrate the value of automated verification in Chapter 5.

4 An inhibitor arc connects a place to a transition and defines the property that the transition associated with the inhibitor arc is enabled only when there are no tokens in the input place.


5 The process of generating the new token values would involve actions such as conflict resolution among goals, plans or knowledge-bases, which is a topic outside the scope of our model and this dissertation.



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