Abstract
This paper deals with the problem of discovering rules that govern social interactions and relations in preliteral societies. Two older computer programs are first described which can receive data, possibly incomplete and redundant, representing kinship relations among named individuals. The programs then establish a knowledge base in the form of a directed graph, which the user can query in a variety of ways. Another program, written on the “top” of these (rewritten in LISP), can form concepts of various properties, including kinship relations, of and between the individuals. The concepts are derived from the examples and non-examples of a certain social pattern, such as inheritance, succession, marriage, class (tribe, moiety, clan, etc.) membership, domination-subordination, incest and exogamy. The concepts become hypotheses about the rules, which are corroborated, modified or rejected by further examples and non-examples.
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Dedicated to Claude Levi-Strauss
Nicholas Findler is Research Professor of Computer Science, Director of the Artificial Intelligence Laboratory and Adjunct Professor of Mathematics at Arizona State University. He has worked in various areas of Artificial Intelligence since 1957 and has authored many articles and books. The two most recent books are Contributions to a Computer-Based Theory of Strategies (New York: Springer-Verlag) and An Artificial Intelligence Technique for Information and Fact Retrieval — An Application in Medical Knowledge Processing (Cambridge, MA: MIT Press). His current interests include Artificial Intelligence, Simulation of Cognitive Behavior, Heuristic Programming, Decision Making under Uncertainty and Risk, Theory of Strategies, Computational Linguistics, Information Retrieval, and Expert Systems
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Findler, N.V. Automatic rule discovery for field work in anthropology. Comput Hum 26, 285–292 (1992). https://doi.org/10.1007/BF00054274
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DOI: https://doi.org/10.1007/BF00054274