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Factsheet: Cognitive map / Fuzzy cognitive mapping

 

Definition

Individuals store their own perception of the reality through mental maps (mental models). (Lasut, A., 2005).
The elicitation of mental models through several steps (cognitive mapping techniques) results in cognitive maps.
In cognitive maps, the stored concepts are decoded, analyzed and clearly structured through cause and effect relationships, and this is significantly useful both for individual aims (thorough understanding of complex issues) and in group situations. In group situations, in particular, stakeholders, experts and decision-makers are encouraged to make explicit their own perceptions, facilitating in the same time the discussion on eventual disagreements/conflicts: this allows the group to reach a shared understanding of the problem/situation and to take common decisions.
A cognitive map is constituted by nodes, which represents the concepts and are connected to each other by links (also called edges). The edges are directed to show the directions of the cause-effect relationships.
The simplest cognitice map is the on where the bipolar construct (Brightman, 2005) is applied: the meaning of the concept in each node is emphasized by the contrast pole of the idea. To indicate to which of the two concepts the relationship expressed with the edge refers, a sign in the link is added (positive to indicate that the promoting effect for the first concept is realized, negative to indicate an inhibitory effect of the first concept- that is a promoting effect on the second one).

A very simple example of a Cognitive Map is given in Fig. 1, just to give the reader an idea of what a Cognitive Map is.

Cmap figure 1

Figure 1: A cognitive map of some economic indicators and associated causal links. (Source: Khan et al., 2000)

An extension of the cognitive map is the Fuzzy Cognitive Map, created by the combination of the Cognitive Mapping techniques and some Fuzzy Logic concepts. In the Fuzzy Cognitive Maps, developed initially by Kosko (1986), the links and the initial values of the concept are weighted (between -1 and 1): this allows respectively defining how strongly on concept causes another and analysing the changes in the concept magnitude over the simulation steps (The concepts can be alternatively weighted within the range 0 ÷1.).

Cognitive mapping is a pure qualitative technique: the use of Fuzzy Logic introduces some quantification aspects. In particular, it is possible to simulate a sort of feedback effects due to the changes in concepts or magnitude. This is significantly useful for dynamic system representation. However, it is important to highlight the fact that a real temporal description of the system is not achievable (differently from what happens with differential equations containing explicitly the time variable): this means that the simulation steps don’t have a connection with any time values, but have to be considered as a simple iteration. Few studies have been carried out to try to include time in the Fuzzy Cognitive Mapping (Hagiwara, 1992; Park, 1995; Carvalho, 2001).

Application objectives

Elicitation of SHs knowledge/perspective. Moreover, through questioning on the map structure, the SHs are also encouraged to find new relationships and solutions and to reach a better issue understanding.
Improving the communication between SHs. In depth reflection upon each other maps give also the possibility of finding alternative ways of understanding the problem.
Cognitive Maps serves as basis when policies and management options are discussed: the decision-making process is facilitated and conflict solutions are encouraged.
Options analysis: cognitive mapping techniques allow several options to be examined to see which are the most beneficial and whether more detailed one need to be considered.

Pertinent participation process phase(s)

1- Starting organization

2- Actors analysis, context

3- Diagnostic of the current situation

4- Search of solutions

5- Implementation, evaluation

Application method

Cognitive Mapping Techniques can be used individually; to develop an overview of one’s own view. It can be used in groups for social learning. In both cases a facilitator should support the definition of the problem/topic space and use of the technique.
A useful reference regarding implementing Cognitive Maps is given by Ackermann (1992), who gives straightforward and simple advice in the form of 12 guidelines, supported by an example, and highlights the common errors which may be experienced by novice mappers.

If Fuzzy Cognitive Mapping Techniques are used Balder (2004) states that before drawing a Fuzzy Cognitive Map, it’s final use should have been decided. From an AquaStress point of view this is a task of the case study leader in conjunction with stakeholders.

Application example(s)

In this section, only the examples, which concerns with ecosystems management and/or with water options selection/implementation are reported.
In Lasut (2005) the experience of FEEM (Fondazione Eni Enrico Mattei) in using the Cognitive Mapping Technique as part of NetSyMod methodology is cited. The NetSyMod (Network Analysis – Creative System Modelling) is a tool aimed to support the decision making process thanks also to an effective involvement of Stakeholders and and experts.
Copland et al. (2004) used the Cognitive Mapping Techniques for investigating the problem of sustainable tourism development in Queenstown, a tourist place in New Zealand, with focus on the environmental/ economic and socio-cultural aspects.
Giordano et al. (2004) proposed a Water Community Decision Support System (WCDSS) aimed to promoting the involvement of all the community members in the water management. Their study referred specifically to the Calendaro River Basin in the Apulia Region (Italy).
A successful application of the Fuzzy Cognitive Maps as Knowledge Mapping Systems is the study of Özesmi (1999). The aim of the research was comparing the cognitive maps of SH groups (villager, vacation home owner, NGO Officials and Government Officials) in order to highlight differences and similarities which would have allowed building common strategies for the conservation of Kizilirmak Delta in Turkey. The attention have been focused especially in the local people needs and knowledge. Due to the success of the research, Özesmi applied again this approach to the Ulubat Lake (Özesmi & Özesmi, 2003) and then he thoroughly explained it in a ‘manual’ (Özesmi & Özesmi, 2004).
Hopps et al. (2002) focusing on the Lake Erie (USA) ecosystem have carried out a similar study. The aim was the understanding of the possible future responses of the system to land use management alternatives, nutrient concentrations, disturbances, etc.
Silva (1995) proposed a methodology for aggregation of FCMs characterised by edges with weight given in the interval [0,1] and weight given by linguistic fuzzy quantifiers. He applied the methodology to experts’ cognitive maps dealing with pump station control within a combined sewer.
Finally application of the Fuzzy Cognitive Maps to the case of the management of estuaries in the Netherlands can be found in Wijk (1996).

Example tools

AquaStress contact(s)

Contact: Flavia Camilleri, IRSA, camilleri@irsa.cnr.it

Reference

  • Ackermann, F., Eden, C., Cropper, S., 1992, Getting started with cognitive mapping, Tutorial paper, 7th Young OR Conference. (Available from Banxia Software Ltd.)
  • Brightman, J., 2004, Cognitive mapping: theory and practice, Value Magazine, 5 pages. (Available as PDF from http://www.banxia.com/demos/trainingmaterial.html)
  • Balder, D., 2004, Fuzzy Cognitive Maps and their uses as Knowledge mapping Systems and Decision Support Systems, http://student.science.uva.nl/~dbalder/media/fcm.pdf
  • Carvalho, J.P., Tomè, J.A.B., 2001, Rule Based Fuzzy Cognitive Maps – Expressing Time in Qualitative System Dynamics. Proceedings of the FUZZ-IEEE 2001.Hagivara, M. 1992. “Extended fuzzy cognitive maps”, in Proc. 1st IEEE Int. Conf. Fuzzy. Syst, New York, NY, March 1992, 795-801.
  • Copland, P., Garnham, B. and Cavana, R., 2004, Sustainable tourism in Queenstown: an application of cognitive strategic mapping. in Smith, K.A. and Schott, C. (eds) , 2004, Proceedings of the New Zealand Tourism and Hospitality Research Conference 2004. Wellington, 8-10 December. pp. 43-54.
  • Lasut, A., 2005, Creative thinking and Modelling for Decision Support in Water Management, FEEM, Nota di Lavoro 81.2005.
  • Giordano, R., Passarella, G., Uricchio, V. F., Vurro, M., 2004, A Community Decision Support System to Enhance Stakeholders` Participation in Water Resources Management, In: Pahl-Wostl, C., Schmidt, S., Rizzoli, A.E. and Jakeman, A.J. (eds), Complexity and Integrated Resources Management, Transactions of the 2nd Biennial Meeting of the International Environmental Modelling and Software Society, iEMSs: Manno, Switzerland, 2004, ISBN 88-900787-1-5, p. 247-252.
    Hobbs, B.F., S.A. Ludsin, R.L. Knight, P.A. Ryan, J. Biberhofer, J.J.H. Ciborowski, 2002, Fuzzy cognitive mapping as a tool to define management objectives for complex ecosystems, Ecological Applications 12 (5): 1548-1565
  • Khan, M. S., Chong, A. and Gedeon, T., 2000, A Methodology for Developing Adaptive Fuzzy Cognitive Maps for Decision Support, Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.4, No.6 pp. 403-407.
  • Kosko, B., 1986, Fuzzy cognitive maps, International Journal of Man-Machine Studies 24: 65-75.
  • Özesmi, U., 1999, Ecosystems in the Mind: Fuzzy Cognitive Maps of the Kizilirmak Delta Wetlands in Turkey http://env.erciyes.edu.tr/Kizilirmak/UODissertation.html
    Özesmi, U., S. Özesmi, 2003, A participatory approach to ecosystem conservation: Fuzzy cognitive maps and stakeholder group analysis in Uluabat Lake, Turkey, Environmental Management 31 (4): 518-531
  • Özesmi, U., S.L. Özesmi, 2004, Ecological models based on people’s knowledge: a multi-step fuzzy cognitive mapping approach, Ecological Modelling 176 (1-2): 43-64
  • Park, K.S., 1995, Fuzzy Cognitive Maps Considering Time Relationships, International Journal of Human Computer Studies, February 1995, pp. 157-167.
  • Silva, P. C., 1995, New Forms of Combined Matrices of Fuzzy Cognitive Maps , Proc. IEEE Int. Conf. on Neural Networks, Vol.2, 1995 pp.771-776.
  • Wijk, M.T.v. and M. van der Tol, 1996, Toepassing van Fuzzy Congnitive Maps ten behoeve van systeem- en beleidsanalyse, Rijkswaterstaat, Rijksinstituut voor Kust en Zee (RIKZ), The Netherlands RIKZ/OS-96.144X.