Artificial Intelligence and cognitive science are the two fields devoted to the study and development of knowledge-based systems (KBS). Over the past 25years, researchers have proposed several approaches for modeling knowledge in KBS, including several kinds of formalism such as semantic networks, frames, and logics. In the early 1980s, J.F. Sowa introduced the conceptual graph (CG) theory which provides a knowledge representation framework consisting of a form of logic with a graph notationand integrating several features from semantic net and frame representations. Since that time, several research teams over the world have been working on the application and extension of CG theory in various domains ranging from natural language processing to database modeling and machine learning. This volume contains selected papers fromthe international conference on Conceptual Structures held in the city of Quebec, Canada, August 4-7, 1993. The volume opens with invited papers by J.F. Sowa, B.R. Gaines, and J. Barwise.
This book constitutes the refereed proceedings of the 18th Conference of the Canadian Society for Computational Studies of Intelligence, Canadian AI 2005, held in Victoria, Canada in May 2005. The revised full papers and 19 revised short papers presented were carefully reviewed and selected from 135 submission. The papers are organized in topical sections on agents, constraint satisfaction and search, data mining, knowledge representation and reasoning, machine learning, natural language processing, and reinforcement learning.
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