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Developing an Agent-Based Model on How Different Individuals Solve Complex Problems

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DOI: 
http://dx.doi.org/10.3926/jiem.1197
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Abstract (2. Language): 
Purpose: Research that focuses on the emotional, mental, behavioral and cognitive capabilities of individuals has been abundant within disciplines such as psychology, sociology, and anthropology, among others. However, when facing complex problems, a new perspective to understand individuals is necessary. The main purpose of this paper is to develop an agentbased model and simulation to gain understanding on the decision-making and problem-solving abilities of individuals. Design/methodology/approach: The micro-level analysis modeling and simulation paradigm Agent-Based Modeling Through the use of Agent-Based Modeling, insight is gained on how different individuals with different profiles deal with complex problems. Using previous literature from different bodies of knowledge, established theories and certain assumptions as input parameters, a model is built and executed through a computer simulation. Findings: The results indicate that individuals with certain profiles have better capabilities to deal with complex problems. Moderate profiles could solve the entire complex problem, whereas profiles within extreme conditions could not. This indicates that having a strong predisposition is not the ideal way when approaching complex problems, and there should always be a component from the other perspective. The probability that an individual may use these capabilities provided by the opposite predisposition provides to be a useful option. Originality/value: The originality of the present research stems from how individuals are profiled, and the model and simulation that is built to understand how they solve complex problems. The development of the agent-based model adds value to the existing body of knowledge within both social sciences, and modeling and simulation.
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REFERENCES

References: 

Abrahamson, D., & Wilensky, U. (2005). Piaget? Vygotsky? I’m game!: Agent-based modeling
for psychology research. Jean Piaget Society Meeting, Canada.
Augier, M., Shariq, S.Z., & Vendele, M.T. (2001). Understanding context: its emergence,
transformation and role in tacit knowledge sharing. Journal of Knowledge Management, 5(2),
125-137. http://dx.doi.org/10.1108/13673270110393176
Balci, O. (1997). Verification, validation and accreditation of simulation models. Proceedings of
the 1997 Winter Simulation Conference. S. Andradottir, K. J. Healy, D. H. Withers and B. L.
Nelson (Eds.). 135-141.
Bandura, A. (2001). Social cognitive theory: An agentic perspective. Annual Review of
Psychology, 52, 1-26. http://dx.doi.org/10.1146/annurev.psych.52.1.1
Bar-Yam, Y. (1993). Dynamics of complex systems. Westview Press.
Bonabeau, E. (2002). Agent-based modeling: Methods and techniques for simulating human
systems. Proceedings of the National Academy of the Sciences, 99(3), 7280-7287.
http://dx.doi.org/10.1073/pnas.082080899
Bossel, H. (1994). Modeling and Simulation. A.K. Peters, Ltd. http://dx.doi.org/10.1007/978-3-663-
10822-1
Bozkurt, I., Padilla, J.J., & Sousa-Poza, A.A. (2007). Philosophical Profile of the Individual. IEEE
Engineering Management Conference, Austin, TX, pp. 42-48.
Cooper, A.C., Folta, T.B., & Woo. C. (1995). Entrepreneurial information search. Journal of
Business Venturing, 10, 107-120. http://dx.doi.org/10.1016/0883-9026(94)00022-M
Davis, J.H. (1969). Individual-group problem solving, subject preference and problem type.
Journal of Personality and Social Psychology, 13(4), 362-374. http://dx.doi.org/10.1037/h0028378
Duncan, R.B. (1972). Characteristics of organizational environments and perceived
environmental uncertainty. Administrative Science Quarterly, 17, 313-327.
http://dx.doi.org/10.2307/2392145
Egges, A., Kshirsagar, S., & Magnenat-Thalmann, N. (2003). A model for personality and
emotion simulation. Knowledge-Based Intelligent Information & Engineering Systems,
453-461.
Epstein, J.M. (1999). Agent-based computational models and generative social science.
Complexity, 4(5), 41-60.
http://dx.doi.org/10.1002/(SICI)1099-0526(199905/06)4:5<41::AID-CPLX9>3.0.CO;2-F
Flood, R.L., & Carson, E.R. (1993). Dealing with Complexity: An Introduction to the Theory
and Application of Systems Science. New York: Plenum Press. http://dx.doi.org/10.1007/978-1-
4757-2235-2
Funke, J. (1991). Solving complex problems: Exploration and Control of Complex Systems. In
R.J. Sternberg and P.A. Frensch (eds.). Complex Problem Solving: Principles and
Mechanisms. Mahwah, NJ: Erlbaum.
Ghasem-Aghaee, N., & Oren, T.I. (2007). Cognitive complexity and dynamic personality in
agent simulation. Computers in Human Behavior, 23, 2983-2997.
http://dx.doi.org/10.1016/j.chb.2006.08.012
Gigliotta, O., Miglino, O., & Parisi, D. (2007). Groups of Agents with a Leader'. Journal of
Artificial Societies and Social Simulation, 10(4), 1. http://jasss.soc.surrey.ac.uk/10/4/1.html.
Retrieved on 10/07/2014.
Gilbert (2008). Researching social life. 3rd Ed., London: Sage.
Gilbert, N, & Abbot, A. (2005). Introduction to special issue: social science computation.
American Journal of Sociology, 110(4), 859-863. http://dx.doi.org/10.1086/430413
Gilbert, N., & Terna, P. (2000). How to build and use agent-based models in social science.
Mind and Society, 1(1), 57-72. http://dx.doi.org/10.1007/BF02512229
Gilbert, N., & Troitzsch, K.G. (2005) Simulation for the social scientist. 2nd edition.
Buckingham: Open University Press.
Gratch, J., & Marsella, S. (2005). Evaluating a computational model of emotion. Autonomous
Agents and Multi-Agent Systems, 11, 23-43. http://dx.doi.org/10.1007/s10458-005-1081-1
Holland, J. (1995). Hidden order: How adaptation builds complexity. Cambridge, MA: Perseus.
Hood, J.N., Logsdon, J.M., & Thompson, J.K. (1993). Collaboration for social problem-solving:
A process model. Business and Society, 32(1), 1-17. http://dx.doi.org/10.1177/000765039303200103
Jennings, N.R., Sycara, K., & Woolridge, M. (1998). A roadmap of agent research and
development. Autonomous Agents and Multi-Agent Systems, 1, 7-38.
http://dx.doi.org/10.1023/A:1010090405266
Kauffman, S. (1995). At home in the universe. NY: Oxford.
Kleijnen, J.P.C. (1999). Validation of models: Statistical techniques and data availability. P.A.
Farrington, H.B. Nembhard, D.T. Sturrock & G.W. Evans (Eds.). Proceedings of the 1999
Winter Simulation Conference, 647-654.
Kikuchi, T., & Nakamori, Y. (2007). Agent model analysis to explore effects of interaction and
environment on individual performance. Journal of Systems Science and Complexity, 20(1),
1-17. http://dx.doi.org/10.1007/s11424-007-9000-y
Kuppers, G., & Lenhard, J. (2005). Validation of simulation: Patterns in the social and natural
sciences. Journal of Artificial Societies and Social Simulation, 8(4), 1-13.
Lawrence, P.R., & Lorsch, J.W. (1967) Organization and environment. Boston. Harvard
University, Graduate School of Business Administration, Division of Research.
Lloyd, I. (1978). Don't define the problem. Public Administration Review, 38(3), 283-286.
http://dx.doi.org/10.2307/975684
Macal, C.M., & North, M.J. (2005). Tutorial on agent-based modeling and simulation. M.E. Kuhl,
N.M. Steiger, F.B. Armstrong & J.A. Joines (Eds). Proceedings of the 2005 Winter Simulation
Conference, 2-15. http://dx.doi.org/10.1109/WSC.2005.1574234
Macal, C.M., & North, M.J. (2007). Agent-based Modeling and Simulation: Desktop ABMS.
Proceedings of the 2007 Winter Simulation Conference. Eds. S. G. Henderson, B. Biller, M.-H.
Hsieh, J. Shortle, J. D. Tew, and R. R. Barton, 95-106. Washington, DC.
http://dx.doi.org/10.1109/WSC.2007.4419592
Martinez-Miranda, J., & Aldea, A. (2005). Emotions in human and artificial intelligence.
Computers in Human Behavior, 21, 323-341. http://dx.doi.org/10.1016/j.chb.2004.02.010
Mumford, E. (1998). Problems, knowledge, solutions: Solving complex problems. Journal of
Strategic Information Systems, 7, 255-269. http://dx.doi.org/10.1016/S0963-8687(99)00003-7
Overwalle, F.V., & Heylighen, F. (2006). Talking nets: A multiagent connectionist approach to
communication and trust between individuals. Psychological Review, 113(3), 606-627.
http://dx.doi.org/10.1037/0033-295X.113.3.606
Peshkin, A. (1993). The goodness of qualitative research. Educational Researcher, 22(2),
23-29. http://dx.doi.org/10.3102/0013189X022002023
Quesada, J., Kintsch, W., & Gomez, E. (2005). Complex problem-solving: A field in search of a
definition? Theoretical issues in ergonomics science, 6(1), 5-33.
http://dx.doi.org/10.1080/14639220512331311553
Rittel, H.W.J. & Webber, M.M. (1973). Dilemmas in a general theory of planning. Policy
Sciences, 4, 155-169. http://dx.doi.org/10.1007/BF01405730
Sallach, D., & Macal, C. (2001). The simulation of social agents: An introduction. Social
Science Computer Review, 19(3), 245-248. http://dx.doi.org/10.1177/089443930101900301
Sargent, R.G. (1999). Validation and verification of simulation models. P.A. Farrington, H.B.
Nembhard, D.T. Sturrock & G.W. Evans (Eds.). Proceedings of the 1999 Winter Simulation
Conference, 39-48.
Simon, H.A. (1972). Theories of Bounded Rationality. Chapter 8 in C.B. McGuire & R. Radner,
(Eds.). Decision and Organization. Amsterdam: North-Holland Publishing Company.
Silverman, B.G., Bharathy, G.K., & Nye, B. (2007). Profiling is politically ‘Correct’: Agent-based
modeling of ethno-political conflict. Interservice/Industry Training, Simulation and Education
Conference.
Smith, E.R., & Conrey, F.R. (2007) Agent-Based Modeling: A New Approach for Theory Building
in Social Psychology. Personality and Social Psychology Review, 11(1), 87-104.
http://dx.doi.org/10.1177/1088868306294789
Steinberg, E.R. (1983). Problem complexity and the transfer of strategies in computerpresented
problems. American Educational Research Journal, 20(1), 13-28.
http://dx.doi.org/10.3102/00028312020001013
Swinth, R.L. (1971). Organizational joint problem-solving. Management Science, 18(2), 68-79.
http://dx.doi.org/10.1287/mnsc.18.2.B68
Sun, R., & Naveh, I. (2004). Simulating Organizational Decision-Making Using a Cognitively
Realistic Agent Model. Journal of Artificial Societies and Social Simulation, 7(3).
http://jasss.soc.surrey.ac.uk/7/3/5.html
Todd, P.M., Billari, F.C., & Simao, J. (2005). Aggregate age-at-marriage patterns from individual
mate-search heuristics. Demography, 42(3), 559-574. http://dx.doi.org/10.1353/dem.2005.0027
Trochim, W.M.K. (2006). Research methods knowledge base.
http://www.socialresearchmethods.net. Retrieved on 10/07/2014.
Wilensky, U. (1999). NetLogo. http://ccl.northwestern.edu/netlogo. Center for Connected
Learning and Computer-Based Modeling. Northwestern University, Evanston, IL.
Wilson, R. (2007). Simulating the Effect of Social Influence on Decision-Making in Small, Task-
Oriented, Groups. Journal of Artificial Societies and Social Simulation 10(4), 4.
http://jasss.soc.surrey.ac.uk/10/4/4.html. Retrieved on 10/07/2014.
Yin, R. K. (2003). Case study research: Design and methods. Applied Social Research Methods
Series, Vol. 5, 3rd Ed. Sage.

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