Proceedings of the Annual Meeting of the Cognitive Science Society

uKLONE is the first sub-symbolic connectionist systenm for reasoning about high level knowledge to approach the representational power of current symbolic AI systems. The algorithm for building a network takes as input a knowledge base definition in a language very similar to that of KL2, which has previously been implemented orJy in Lisp. In nXLONE, a concept is more than a set of features: it is a complex of required and optional subparts filling well defined roles, each of which may have its own type restrictions. In addition to being able to use complex structured descriptions in its reasoning, ^iKLONE exhibits a facility for plausible inference due to its inherently parallel constraint satisfaction algorithm that is not shared by symbolic systems. This paper describes h o w the system answers a query that requires both of these characteristics. It is hoped that this is the beginnings of a response to (McDermott, 1986)'s challenge that connectionists should pay more attention to architectural issues and rely less onlearrung.