Abstract. Computer-based Expert Systems that use knowledge, facts, and reasoning techniques
to solve problems, normally requiring the abilities of human experts, are increasingly
being used in many activities. The United Nations University (UNU) Agroforestry Expert
System (AES) is a first attempt to apply this technique to agroforestry. UNU-AES is a
prototype Knowledge-Based Expert System (KBES) designed to support land-use (agricultural,
forestry, etc.) officials, research scientists, farmers, and individuals interested in maximizing
benefits gained from applying agroforestry management techniques in developing countries.
This prototype addresses the options for alley cropping, a promising agroforestry
technology which has potential applicability when used under defined conditions in the tropics
and subtropics. Alley cropping involves the planting of crops in alleys or interspaces between
repeatedly pruned hedgerows of fast-growing, preferably leguminous, woody perennials. The
primary benefits from this technique include nutrient enrichment, soil improvement, and
erosion control. UNU-AES, which is the first known attempt at the application of expert
system procedures in the field of agroforestry, uses a total of 235 decision rules to develop its
recommendations. With the inclusion of more climatic and socio-economic data and improved
advisory recommendations, UNU-AES can be expanded to provide advice on alley
cropping in more diverse geographical and ecological conditions and eventually address other
agroforestry techniques.
Introduction
This paper describes the preliminary results of the efforts to develop a
Knowledge-Based Expert System (KBES) for agroforestry. Known as the
United Nations University Agroforestry Expert System (UNU-AES), its
goal is to assist individuals in applying the agroforestry approaches to land
management for sustainable production of food and fuelwood supplies by
farmers in developing countries.
An Expert System is a computer program that uses knowledge, facts, and
reasoning techniques to solve problems that normally require the abilities of