Analysis of Farmers’ Concepts of Environmental Management Measures: An Application of Cognitive Maps and Cluster Analysis in Pursuit of Modelling Agents’ Behaviour

The Common Agricultural Policy (CAP) of the European Union (EU) recognises that agriculture is multifunctional and that its multifunctional nature should be promoted. Under this expectation, Europe’s agricultural areas are required to provide a diverse mixture of market and non-market goods for the private benefit of agricultural businesses on the one hand, and public good on the other. For reasons that are very well understood, a completely liberalised agricultural market cannot be relied on to provide many of the non-market and public goods expected from a multifunctional agriculture, and, given this, some form of regulation of the market or governmental involvement in it is inevitable. One way to view the CAP, then, is as the mechanism by which the public buys non-market goods from Europe’s farmers at a price which is sufficient to have them forego alternative activities which produce no public good. The aim of policy optimisation for the CAP, when viewed in this context, is to allow the public to purchase the maximum amount of good for the least cost and to compensate those farmers who are really contributing to social welfare.

[1]  J. Charlesworth Contemporary political analysis , 1967 .

[2]  Mark Rounsevell,et al.  Are agricultural land use patterns influenced by farmer imitation , 2006 .

[3]  Wojtek J. Krzanowski,et al.  Principles of multivariate analysis : a user's perspective. oxford , 1988 .

[4]  François Bousquet,et al.  Multi-agent simulations and ecosystem management: a review , 2004 .

[5]  P. Vereijken,et al.  A methodic way to more sustainable farming systems , 1992 .

[6]  J. Gareth Polhill,et al.  Agent-based land-use models: a review of applications , 2007, Landscape Ecology.

[7]  Mark Ettinger The complexity of comparing reaction systems , 2002, Bioinform..

[8]  Bart Kosko,et al.  Fuzzy Cognitive Maps , 1986, Int. J. Man Mach. Stud..

[9]  B. McCarl,et al.  The Potential Role of Multilevel Programming in Agricultural Economics , 1981 .

[10]  Michalis Glykas,et al.  A soft knowledge modeling approach for geographically dispersed financial organizations , 2005, Soft Comput..

[11]  Panagiotis Chytas Performance measurement in a Greek financial institute using the balanced scorecard , 2006 .

[12]  G. Marshall,et al.  Ecological Management of Crop-Weed Interactions , 2001 .

[13]  Panagiotis Chytas,et al.  Intelligent impact assessment of HRM to the shareholder value , 2008, Expert Syst. Appl..

[14]  M. Janssen,et al.  Multi-Agent Systems for the Simulation of Land-Use and Land-Cover Change: A Review , 2003 .

[15]  Uygar Özesmi,et al.  Ecological models based on people’s knowledge: a multi-step fuzzy cognitive mapping approach , 2004 .

[16]  Chrysostomos D. Stylios,et al.  Fuzzy Cognitive Maps in modeling supervisory control systems , 2000, J. Intell. Fuzzy Syst..

[17]  Rod Taber,et al.  Knowledge processing with Fuzzy Cognitive Maps , 1991 .

[18]  Peter Cheeseman,et al.  Fuzzy thinking , 1995 .

[19]  Gareth Hughes,et al.  Killing or culling? Is it possible to manage weeds as a resource? , 2001 .

[20]  S. Phillips,et al.  Processing capacity defined by relational complexity: implications for comparative, developmental, and cognitive psychology. , 1998, The Behavioral and brain sciences.

[21]  Manjula Dissanayake,et al.  Qualitative simulation of construction performance using fuzzy cognitive maps , 2007, 2007 Winter Simulation Conference.

[22]  Richard L. Tweedie,et al.  Markov Chains and Stochastic Stability , 1993, Communications and Control Engineering Series.

[23]  Bart Kosko,et al.  Virtual Worlds as Fuzzy Cognitive Maps , 1994, Presence: Teleoperators & Virtual Environments.

[24]  John B. Bowles,et al.  Using Fuzzy Cognitive Maps as a System Model for Failure Modes and Effects Analysis , 1996, Inf. Sci..

[25]  Voula C. Georgopoulos,et al.  Fuzzy cognitive map architectures for medical decision support systems , 2008, Appl. Soft Comput..

[26]  M. Hill,et al.  Weeds in fields with contrasting conventional and genetically modified herbicide-tolerant crops. II. Effects on individual species. , 2003, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[27]  B Kosko,et al.  Adaptive bidirectional associative memories. , 1987, Applied optics.

[28]  R. May,et al.  Stability and Complexity in Model Ecosystems , 1976, IEEE Transactions on Systems, Man, and Cybernetics.