Toward Automated Discovery in the Biological Sciences

Knowledge discovery programs in the biological sciences require flexibility in the use of symbolic data and semantic information. Thus, the framework for the discovery program must facilitate proposing and selecting the next task to perform and performing the selected tasks. The framework we describe, called the agenda- and justificationbased framework, has several properties that are desirable in semiautonomous discovery systems: It provides a mechanism for estimating the plausibility of tasks, it uses heuristics to propose and perform tasks, and it facilitates the encoding of general discovery strategies and the use of background knowledge. Our results demonstrate that both reasons given for performing tasks and estimates of the interestingness of the concepts and hypotheses examined by HAMB contribute to its performance and that the program can discover novel, interesting relationships in biological data.