Automated Reasoning for Biology and Medicine

Eric Horvitz

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During the last decade, computer scientists have made significant progress in developing techniques for storing and retrieving information, and for solving difficult inferential problems with computer-based reasoners. The growth in the power of computer processors, and the parallel decline of the cost of computer memory, has catalyzed the development of innovative software for problem solving. In particular, there have been promising advances in computational methods for acquiring, representing, and manipulating biological and medical information. I will present key concepts of automated reasoning investigated in the computer-science subdiscipline called artificial intelligence (AI). I will frame my discussion in terms of the genesis and maturation of AI and related subdisciplines that were spawned shortly after the development of electronic computers, and will review key themes that have dominated research over the last three decades.(40 pages)

Keywords: Introduction to artificial intelligence, history of artificial intelligence, history of intelligent reasoning research, logical reasoning, expert systems, Bayesian networks, influence diagrams.

In: Advances in Computer Methods for Systematic Biology: Artificial Intelligence, Databases, and Computer Vision, Johns Hopkins University Press, 1993. Invited opening talk, Conference on AI in Systematic Biology, Napa Valley, California, September 1990. Also, Stanford CS Technical Report KSL-92-55.

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