Åbo Akademi

Department of Information Systems

 

4054 Intelligent Systems in Business (5cr)

Autumn 2000
 

Aims


The course aims at deepening the participants’ knowledge in modern computer supported problem solving. We look at the state of the art in advanced knowledge-based systems, at new technological developments and emerging paradigms in intelligent systems.
 

Contents:

 

Literature:

Book:

  1. Dhar, V. and Stein, R. Intelligent Decision Support Systems, Prentice Hall, 1997.

Articles:

Knowledge-based systems

  1. Hayes-Roth, F. Jacobstein, N., The State of Knowledge-Based Systems, Communications of the ACM, March 1994, Vol. 37, No. 3, pp. 27-39.
  2. Luconi, F.L. & Malone, T.W. and Scott Morton, M.S., Expert Systems: The next challenge for managers. In Decision Support Systems, Putting Theory into Practice, ed. by Sprague, R.H. and Watson, H.J. Prentice Hall, 1993. pp.365-378.
  3. Gill, G., Early Expert Systems: Where Are They Now? MIS Quarterly, March 1995 pp. 51-81.
  4. Guimares, T. Yoon, Y. Clevenson, A., Factors important to expert systems success. A field test. Information & Management, Vol 30, 1996, pp. 119-130.
  5. Allen, B. Case-Based Reasoning: Business applications, Communications of the ACM, March 1994, Vol. 37, No. 3, pp. 41-42.

Neural Networks

  1. Rumelhart, D.Widrow Bernard, Lehr Michael, The Basic Ideas in Neural Networks, Communications of the ACM, March 1994/Vol. 37, No. 3, pp. 87-91.
  2. Rumelhart, D.Widrow Bernard, Lehr Michael, Neural Networks: Applications in Industry, Business and Science, Communications of the ACM, March 1994, Vol. 37, No. 3, pp. 93-105.
  3. Wong, B, Yakup, S. Neural Networks Applications in Finance: A Review and Analysis of Literature (1990-1996), Information & Management, 1998 No. 34, pp. 129-139.
  4. Sinkkonen, J and Lahtinen, I. Hermoverkot markkinoinnin apuna, MikroPC , 1998, No.4
  5. Kohonen, T. The Self-Organizing Map, Proceedings of the IEEE, September 1990, Vol 78, No.9, pp. 1464-78.
  6. Li, E., Arificial Neural Networks and Their Business Applications, Information & Management, 1994, No. 27 pp. 303-313.

Genetic Algorithms

  1. Kassicieh, S., Paez, T. and Vora, G. Investment Decisions Using Genetic Algorithms, IEEE Expert 1997, pp. 484-490.
  2. Back, B. Laitinen, T. and Sere, K. Neural Networks and Genetic Algorithms for Bankruptcy Predictions. Proceedings on World Conference on Expert Systems, 1992, pp. 123-130.
  3. Goldberg, D. Genetic and Evolutionary Algorithms Come of Age, Communications of the ACM, March 1994, Vol. 37, No. 3, pp. 113-119.
  4. Kumar, N. Krovi, R., Rajagoplan, B. : Financial Decision Support with Hybrid Genetic and Neural Based Modeling Tools, European Journal of Operations Research, 1997, No.103, pp. 339-349.

Intelligent Agents

  1. Maes, P. Guttman, R. Moukas, A.: Agents that Buy and Sell, Communications of the ACM, March 1999, Vol.42, No 3, pp. 81-91.
  2. Glushko, R. Tenenbaum, J., Meltzer, B.: An XML Framework for Agent-based E-commerce, Communications of the ACM, March 1999, Vol.42, No 3, pp. 106-114.
  3. Liu, S., Business Environment Scanner for Senior Managers: Towards Active Executive Support with Intelligent Agents, Expert Systems with Applications, 1998, Vol 15, pp. 111-121.
  4. Hattori, F. Oghuro, T. Yokoo, M. Matsubara, s. Yoshida, S.: Socialware: Multiagent Systems for Supporting, Communications of the ACM, March 1999, Vol.42, No 3, pp. 55-61.
  5. Brown, C. Gasser, L., O’Leary, D. and Sangster A.: AI on the WWW, Supply and Demand Agents. IEEE Expert, August 1995, pp. 50-55.
Software: XpertRule, Neuralyst, Som_Pak
 

Examination:


4054.1 Part I 3 cr. Written examination (max 60 points) on October 26th 15-19 in DC 3223. 10 points can be earned during the lecture period by discussing and turning in 4 exercises during the lectures.

4054.2 Part II 2 cr. Software application developments, presentation and documentation (max 40 points).

Minimum points required to pass are 50% from each part.
 
 
 

Schedule Autumn 2000:

 

Time                 Place             Topic


12.9 14-15             DC3223                Overview of the course

14.9 15-17             DC3223                Knowledge-based systems

19.9 14-16             DC3223                Knowledge-based systems

21.9 15-17             DC 3223               Exercise 1. Overview of Neural Networks

26.9 14-16             DC 3223               Neural Networks; Backpropagation

28.9 15-17             DC 3223               Neural Networks, SOM Demo SOM_PAK

3.10 14-16             DC 3223               Exercise 2. Genetic Algorithms

5.10 15-17             DC 3223               Agent technology

10.10 14-16           Dilbert                   Demo XpertRule

12.10 15-17           Dilbert                   Demo Neuralyst

17.10 14-16           DC 3223               Exercise 3 and 4. Delivery of assignments

24.10 14-18           DC3223                Written Exam

26.10 —22.11       Course work on software applications

22.11 15-18          DC3223 Demo of assignments

Responsible: Professor Barbro Back, email: Barbro Back@abo.fi (Part I)

EM Francisco Alcaraz email: Falcaraz@abo.fi (Part II)