Hyperknowledge representation: challenges and promises

Hyperknowledge is formed as a system of sets of interlinked concepts, much in the same way as hypertext is built with interlinked text strings; then hyperknowledgefunctions would be constructs which link concepts / systems of concepts in some predetermined or wanted way. Under hyperknowledge representation we mean the identification (or approximation) of hyperknowledge-functions in order to explain, describe and predict the behavoir of the real-life system. Depending on the environment one can use first-order logic, production systems, semantic nets, frames, fuzzy sets, neural networks, neural fuzzy systems, Bayes’ rules, rough sets, belief networks, certainty factors, incidence calculus, modal logics, cognitive maps, etc. In this paper we will briefly address the following methods of (hyper)knowledge representation: • First-order logic provides a language for expressing knowledge and principles for manipulating expressions from this language. • In production systems the knowledge of experts is expressed in the form of crisp IF-THEN rules, and production rules are treated as independent pieces of knowledge. • Fuzzy logic performs an inference mechanism under cognitive uncertainty, where the uncertainty is represented by linguistic variables whose terms are characterized by fuzzy subsets or possibility distributions. • Neural networks can be considered as simplified mathematical models of brainlike systems and they function as parallel distributed computing networks. They can learn new associations, new functional dependencies and new patterns. • Neural fuzzy systems incorporate the concept of fuzzy logic into the neural networks to enable a system dealing with cognitive uncertainties in a manner more like humans. • Cognitive maps can represent crisp cause-effect relationships which are perceived to exist among the elements of a given environment. Fuzzy cognitive maps are fuzzy signed directed graphs with feedbacks, and they model the world as a collection of concepts and causal relations between concepts. ∗Presently Donner Visiting Chair at Åbo Akademi University. †in: P.Walden, M.Brännback, B.Back and H.Vanharanta eds., The Art and Science of DecisionMaking, Åbo Akademi University Press, Åbo, 1996 61-89.