A Reasoning Model Based on Perennial Crop Allocation Cases and Rules

This paper presents a prototype of case-based reasoning, built for the agricultural domain. Its aim is to forecast the allocation of a new energy crop, the miscanthus. Interviews were conducted with french farmers in order to know how they make their decisions. Based on interview analysis, a case base and a rule base have been formalized, together with similarity and adaptation knowledge. Furthermore we have introduced variations in the reasoning modules, for allowing different uses. Tests have been conducted. Results showed that the model can be used in different ways, according to the aim of the user, and e.g. the economic conditions for miscanthus allocation.

[1]  Christopher K. Riesbeck,et al.  Inside Case-Based Reasoning , 1989 .

[2]  Agnar Aamodt,et al.  Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches , 1994, AI Commun..

[3]  Agnar Aamodt,et al.  CASE-BASED REASONING: FOUNDATIONAL ISSUES, METHODOLOGICAL VARIATIONS, AND SYSTEM APPROACHES AICOM - ARTIFICIAL INTELLIGENCE COMMUNICATIONS , 1994 .

[4]  Roger C. Schank,et al.  Inside case-based explanation , 1994, Artificial intelligence series.

[5]  Will Allen,et al.  Using case-based reasoning methodology to maximise the use of knowledge to solve specific rangeland problems☆ , 1997 .

[6]  Karl Branting,et al.  CARMA: A Case-Based Range Management Advisor , 2001, IAAI.

[7]  Kevin D. Ashley,et al.  The Role of Information Extraction for Textual CBR , 2001, ICCBR.

[8]  S. Bellon,et al.  Categorising combinations of farmers' land use practices: an approach based on examples of sheep farms in the south of France , 2001 .

[9]  Deborah L. McGuinness,et al.  Knowledge Provenance Infrastructure , 2003, IEEE Data Eng. Bull..

[10]  Florence Le Ber,et al.  Modeling and Comparing Farm Maps using Graphs and Case-based Reasoning , 2003, J. Univers. Comput. Sci..

[11]  David McSherry,et al.  Introduction to the Special Issue on Explanation in Case-Based Reasoning , 2005, Artificial Intelligence Review.

[12]  Luc Lamontagne,et al.  Case Retrieval Reuse Net (CR2N): An Architecture for Reuse of Textual Solutions , 2009, ICCBR.

[13]  A. Arneth,et al.  Representing human behaviour and decisional processes in land system models as an integral component of the earth system , 2011 .

[14]  J. Carbonell,et al.  Learning by Analogy: Formulating and Generalizing Plans from Past Experience , 1983 .

[15]  P. Verburg,et al.  Spatially explicit modelling of biofuel crops in Europe , 2011 .

[16]  Y. Sun,et al.  Integrating spatial relations into case-based reasoning to solve geographic problems , 2012, Knowl. Based Syst..

[17]  Laura Martin,et al.  Perennial biomass crop cultivation and its territorial patterns A case-study of miscanthus in Côte-d'Or (Burgundy, France) , 2013 .

[18]  E. Bonari,et al.  Landscape agronomy: a new field for addressing agricultural landscape dynamics , 2012, Landscape Ecology.

[19]  D. Rizzo,et al.  Miscanthus spatial location as seen by farmers : A machine learning approach to model real criteria , 2014 .

[20]  Susan Craw,et al.  Case-Based Reasoning , 2010, Encyclopedia of Machine Learning.