Skip to main content
Log in

Axiomatic agent based architecture for agile decision making in strategic information systems

  • Original Research
  • Published:
Journal of Ambient Intelligence and Humanized Computing Aims and scope Submit manuscript

Abstract

Strategic decisions to be seriously made by strategic information systems (SIS) in uncertain environments are considered as the main concern of organizations to achieve differentiating advantages. Architecting such an SIS in which strategic decisions are made continuously can be well performed by employing an axiomatic design approach by which basic constituents of an agent based SIS are determined. People may decide differently in the same situation not because they are logical but because they sometimes decide emotionally. Here architecting an SIS based on emotional agents which contribute in strategic decision making has been proposed in a model based on axiomatic design theory to consider critical points such as emotional decision making and flexibility which results in agile SIS.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  • Akhgar B (2004) Strategic information systems, concept to code, vol 4. KAR white paper, UK

    Google Scholar 

  • Cicirello VA (2001) A game-theoretic analysis of multi-agent systems for shop floor routing. The Robotics Institute, Carnegie Mellon University, Pittsburgh

    Google Scholar 

  • Davis D, Sloman A, Poli R (1995) Simulating agents and their environments. AISB Q 93:34–41

    Google Scholar 

  • El-Nasr MS., Seif M, Skubic M (1998). A Fuzzy emotional agent for decision-making in a mobile robot. Paper presented at the IEEE International Conference on Fuzzy Systems

  • El-Nasr MS, Yen J, Ioerger TR (2000) FLAME: fuzzy logic adaptive model of emotions. Auton Agents Multi-Agent Syst 3(3):219–257

    Article  Google Scholar 

  • Ferber J (1999) Multi-agent systems. Addison-Wesley, London

    Google Scholar 

  • Gmytrasiewicz PJ, Lisetti CL (2002) Emotions and personality in agent design and modeling. Intell Agents VIII Agent Theor Archit Lang 2333:21–31

    Google Scholar 

  • Jennings NR, Sycara K, Woolridge M (1998) A roadmap of agent research and development. Auton Agent Multi Agent Syst 1:7–38

    Article  Google Scholar 

  • Kalenka S, Jennings NR (1997) Socially responsible decision making by autonomous agents. Springer, Verlag

    Google Scholar 

  • Kulak O, Durmusoglu MB, Tufekci S (2005a) A complete cellular manufacturing system design methodology based on axiomatic design principles. Comput Ind Eng 48(4):765–787. doi:10.1016/j.cie.2004.12.006

    Article  Google Scholar 

  • Kulak O, Kahraman C, Oztaysi B, Tanyas M (2005b) Multi-attribute information technology project selection using fuzzy axiomatic design. J Enterp Inform Manag 18(3):275–288

    Article  Google Scholar 

  • Macas M, Ventura R, Cust′odio L, Pinto-Ferreira C (2001) Experiments with an emotion-based agent using the DARE architecture. Paper presented at the symposium on emotion, cognition and affective computing (AISB’01 Convention), UK

  • Nucci Franco G, Batocchio A (2001) Towards an axiomatic framework to support the design of holonic systems. Paper presented at the database and expert systems applications, 2001. Proceedings 12th International Workshop on database and experts

  • Peshkin L (2003) Reinforcement learning by policy search. Massachusetts Institute of Technology, Artificial Intelligence Laboratory, Cambridge

    Google Scholar 

  • Pinson S, Moraïtis P (1997) An intelligent distributed system for strategic decision making. Group Decis Negot 6(1):77–108

    Article  Google Scholar 

  • Shirazi MA, Soroor J (2007) An intelligent agent-based architecture for strategic information system applications. Knowl Based Syst 20(8):726–735

    Article  Google Scholar 

  • Sloman A (2004) What are emotion theories about? In: Hudlicka E, Cañamero D (eds) Architectures for modeling emotion: cross-disciplinary foundations. AAAI Spring Symposium Technical Report, pp 128–134

  • Sloman A, Croucher M (1981) Why robots will have emotions. In: Proceedings of IJCAI

  • Stone P, Veloso M (2000) Multi agent systems: a survey from a machine learning perspective. Auton Robots 8:345–383

    Article  Google Scholar 

  • Suh NP (1990) The principles of design. Oxford University Press, New York

    Google Scholar 

  • Suh NP (1995) Design and operation of large systems. J Manuf Syst 14(3):203–213

    Article  Google Scholar 

  • Suh NP (1997) Design of Systems. CIRP Ann Manuf Technol 46(1):75–80. doi:10.1016/S0007-8506(07)60779-3

    Article  Google Scholar 

  • Suh NP (1998) Axiomatic design theory for systems. Res Eng Des Theory Appl Concurr Eng 10(4):189–209

    Google Scholar 

  • Suh NP (2001) Axiomatic design: advances and applications. Oxford University Press, New York

    Google Scholar 

  • Sutton RS, Barto AG (1998) Reinforcement learning I: introduction. MIT, USA

    Google Scholar 

  • Togay C, Sundar G, Dogru AH (2006) Detection of component composition mismatch with axiomatic design

  • Turban E, McLean ER, Wetherbe JC (2001) Information technology for management : making connections for strategic advantage, 2nd edn. Wiley, New York

    Google Scholar 

  • Velásquez J (1998) When robots weep: emotional memories and decision-making. In: Proceedings of AAAI-98, Madison, WI

  • Weiss G (1999) Multi agent systems, a modern approach to distributed artificial intelligence. MIT Press, USA

    Google Scholar 

  • Wooldridge M, Jennings NR (1995) Intelligent agent: theory and practice. Knowl Eng Rev 10(2):115–152

    Article  Google Scholar 

  • Wurman PR (1999) Market structure and multidimensional auction design for computational economies. PhD Thesis, University of Michigan

  • Wurman PR, Wellman MP, Walsh WE (2001) A parametrization of the auction design space. Games Economic Behav 35(1–2):304–338

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Esmael Salahi Parvin.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Akhgar, B., Salahi Parvin, E. & Sherkat, M.H. Axiomatic agent based architecture for agile decision making in strategic information systems. J Ambient Intell Human Comput 5, 93–104 (2014). https://doi.org/10.1007/s12652-012-0136-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12652-012-0136-9

Keywords

Navigation