TECHNIQUES OF REPRESENTING KNOWLEDGE IN KNOWLEDGE-BASED SYSTEMS

Increasingly complex decision-making situations increase the probability that wrong choices will be made. Knowledge-based systems can help increase the success rate, thereby improving farm performance. Knowledge-based systems differ according to their construction, the way in which they are programmed, and the mode of representing knowledge that is employed. The representation of knowledge in the form of production rules has established itself as a viable method alongside those models that are based on production functions. The nature of the problem to be solved determines which of the two techniques of representation should be selected. Two concrete examples have been employed to illustrate the methods and techniques involved in the two approaches; the various advantages and disadvantages have been discussed, and it has been shown in conclusion where the pitfalls are and how the advantages of both procedures can be utilized by creating hybrid systems.