Identifying relational error recovery/online plans utilizing fuzzy logic techniques and semantic networks

Abstract

The potential for the use of fuzzy logic in the assignment of fuzzy weights to the existing relational links of the Primitive Structure Database is explored. The assignment of these weights is crucial to establishing robust error recovery and a competent online planning scheme as the weights provide a mechanism whereby the extent of the strength of a relation can be established. Through the appropriate defuzzification of the combined weights in the path of a single plan or multiple plans, a more realistic expectation of the potential success of a particular plan can be extracted than can be expected if the assigned weights were initially crisp numbers. The defuzzified weighting can then be used to hierarchically structure several different plans with differing potentials for success. This hierarchy permits alternative plans to be made available should a plan with the highest potential for success rating field. In addition, a limiting agent (threshold) established through the defuzzification of the relational weights can be used to limit the number of potential plans that will be examined.