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.
Similar content being viewed by others
References
Akhgar B (2004) Strategic information systems, concept to code, vol 4. KAR white paper, UK
Cicirello VA (2001) A game-theoretic analysis of multi-agent systems for shop floor routing. The Robotics Institute, Carnegie Mellon University, Pittsburgh
Davis D, Sloman A, Poli R (1995) Simulating agents and their environments. AISB Q 93:34–41
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
Ferber J (1999) Multi-agent systems. Addison-Wesley, London
Gmytrasiewicz PJ, Lisetti CL (2002) Emotions and personality in agent design and modeling. Intell Agents VIII Agent Theor Archit Lang 2333:21–31
Jennings NR, Sycara K, Woolridge M (1998) A roadmap of agent research and development. Auton Agent Multi Agent Syst 1:7–38
Kalenka S, Jennings NR (1997) Socially responsible decision making by autonomous agents. Springer, Verlag
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
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
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
Pinson S, Moraïtis P (1997) An intelligent distributed system for strategic decision making. Group Decis Negot 6(1):77–108
Shirazi MA, Soroor J (2007) An intelligent agent-based architecture for strategic information system applications. Knowl Based Syst 20(8):726–735
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
Suh NP (1990) The principles of design. Oxford University Press, New York
Suh NP (1995) Design and operation of large systems. J Manuf Syst 14(3):203–213
Suh NP (1997) Design of Systems. CIRP Ann Manuf Technol 46(1):75–80. doi:10.1016/S0007-8506(07)60779-3
Suh NP (1998) Axiomatic design theory for systems. Res Eng Des Theory Appl Concurr Eng 10(4):189–209
Suh NP (2001) Axiomatic design: advances and applications. Oxford University Press, New York
Sutton RS, Barto AG (1998) Reinforcement learning I: introduction. MIT, USA
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
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
Wooldridge M, Jennings NR (1995) Intelligent agent: theory and practice. Knowl Eng Rev 10(2):115–152
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
Author information
Authors and Affiliations
Corresponding author
Rights 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
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12652-012-0136-9