NeuroSymbolic integration with uncertainty

Abstract

Most of the tasks which require intelligent behavior have some degree of uncertainty associated with them. The occurrence of uncertainty might be because of several reasons such as the incomplete domain knowledge, unreliable or ambiguous data due to measurement errors, inconsistent data representation. Most of the knowledge-based systems require the incorporation of some form of uncertainty management, in order to handle this kind of indeterminacy present in the system. In this paper, we present one such method to handle the uncertainty in neurules, a neuro-symbolic integration concept. Neuro-Computing is used within the symbolic frame work for improving the performance of symbolic rules. The uncertainty, the personal belief degree that an uncertain event may occur is managed by computing the composite belief values of incomplete or conflicting data. With the implementation of uncertainty management in neurules, the accuracy of the inference mechanism and the generalization performance can be improved.