Can a large knowledge base be built by importing and unifying diverse knowledge?: lessons from scruffy work

摘要

Two different roads to the modelling of intelligence and the building of intelligence systems have been proposed. These are the ‘neat’ (logical) versus scruffy (ad hoc) philosophies applied to the building of AI systems. The paper revisits this issue, and characterizes the nature of recent relevant work, with particular emphasis on the Cyc project. A constructionist perspective that is akin to Piagetian work and Sowa's crystallizing of theory is espoused. This perspective notes that scruffy, bottom-up methods provide a developmental basis for more formal theories which, in turn, provide a further bootstrapping of subsequent scruffy development of important formal elements, such as conceptual catalogues. Particular emphasis is placed on conceptual analysis results that are available from the Cyc project, which is attempting to achieve robust intelligence using vast pools of handcrafted knowledge. This effort, like a good conceptual catalogue, is an attempt to provide an empirical basis for knowledge acquisition via automated understanding of documentation and machine learning.