Robust initialization for reasoning procedures in a hierarchical heterogeneous knowledge-base

This paper describes a model of a hierarchical, heterogeneous knowledge-base. The proposed model consists of an associative level that is implemented by a Kanerva-like sparse distributed memory (SDM) and a semantic level realized by a knowledge-representation scheme based on the Fuzzy Petri Net theory. The levels are interconnected with forward and backward connections that are used for the robust initialization of multi-reasoning procedures (inheritance, recognition and intersection search) at the semantic level. Multi-reasoning supports reasoning for an unknown concept (i.e., a concept that is not defined at the semantic level), parallel reasoning for more than one concept that is obtained by forward connections from the associative level and used for multiple initialization, and the chaining of associative information retrieval and the reasoning process using forward and backward connections. An example of the initialization of the multi-inheritance procedure is given.