Abstract
This short paper will discuss the background to the special issue through a consideration of the basic knowledge representation issues in AI. We will briefly introduce the symbolic and sub-symbolic representations which are traditionally associated with AI, before noting the socially constructed views of knowledge with which they are at odds and the techniques for knowledge elicitation which they use. This forms the context against which this special issues sits, highlighting the broad view of knowledge elicitation and representation and the issues that they raise which we feel are important to debate in the discipline. By gathering this set of papers together, we hope to encourage researchers to see the value in differing approaches and to encourage a more synthetic view of the discipline, where contributions and insights from different perspectives may be of use.
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References
Abdolmohammadi, M. J. (1987). Decision Support and Expert Systems in Auditing: A Review and Research Directions.Accounting and Business Research, Spring, 173–185.
Agre, P. E. (1988).The Dynamic Structure of Everyday Life. MIT Artificial Intelligence Laboratory Technical Report 1085.
Agre, P. E. and Chapman, D. (1988).What are plans for? MIT AI Memo 1050, September 1988.
Bandler, W. and Kohout, L. J. (1984). The four modes of inference in fuzzy expert systems. In Trappl, R. (ed).Cybernetics and Systems Research 2 (Amsterdam, Holland: Elsevier, North-Holland), 581–586.
Hertz, J., Kroph, A. and Palmer, R. G. (1991). Introduction to the Theory of Neural Computation (Reading, Mass.: Addison Wesley).
Hijikata, M. (1995). Group decision process support system for regional planning: a perspective from Japan.AI and Society, 9, 244–257.
Lave, J. (1988).Cognition in Practice (Cambridge: Cambridge University Press).
Lave, J. and Wenger, E. (1991).Situated Learning: Legitimate Peripheral Participation (Cambridge, UK: Cambridge University Press).
Sol, H. G., Takkenberg, C. A. T. and De Vries Robbé, P. F. (eds) (1987).Expert Systems and Artificial Intelligence in Decision Support Systems. Proceedings of the Second Mini Euroconference, Lunteren, The Netherlands (17–20 November 1985) (Dodrecht, Holland: D. Reidel Publishing Company).
Suchman, L. A. (1987).Plans and Situated Action: The Problem of Human Machine Communication (Cambridge: Cambridge University Press).
Turban, E. (1988).Decision Support and Expert Systems (London, UK: Macmillan).
Turksen, I. B. (1992). Fuzzy Ordinal Models for AI-OR. In Doukidis, G. I. and Paul, R. J. (eds). Artificial Intelligence in Operational Research (Basingstoke, UK:Macmillan Press, Ltd), 115–126.
WCNN95 (1995), World Congress on Neural Networks (Hillsdale, NJ: Lawrence Erlbaum and INNS Press).
WCNN95 (1996). World Congress on Neural Networks (Hillsdale, NJ: Lawrence Erlbaum and INNS Press).
Werbos, P. J. (1996). Learning in the brain: an engineering interpretation. In Pribram, K. (ed).Learning as Self-Organisation (Hillsdale, NJ: Lawrence Erlbaum).
Zadeh, L. A. (1965). Fuzzy Sets.Information and Control, 8, 338–353.
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Paul, R.J., Macredie, R.D. Objective and subjective views of knowledge and their implications for system design. AI & Soc 11, 1–5 (1997). https://doi.org/10.1007/BF02812434
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DOI: https://doi.org/10.1007/BF02812434