Systematic Methods of Scientific Discovery (1995 AAAI Spring Symposium)

DESCRIPTION

Scientific discovery is surely among the most celebrated creative processes. Discovery receives scholarly attention from several disciplines, not least of which is artificial intelligence.

AI has explored the view that much of scientific reasoning is problem solving, and hence is akin to more ordinary types of reasoning. Experience has shown that some scientific reasoning can be automated: research on discovery has already yielded competent programs that, e.g.,, plan organic syntheses, elucidate molecular structure, determine reaction mechanisms, make interesting graph-theoretic conjectures, and detect patterned behavior. Where all this may lead was foreseen by Allen Newell [Artif.Intell.; 25(3) 1985]:

[The field] should, by the way, be prepared for some radical, and perhaps surprising, transformations of the disciplinary structure of science (technology included) as information processing pervades it. In particular, as we become more aware of the detailed information processes that go on in doing science, the sciences will find themselves increasingly taking a metaposition, in which doing science (observing, experimenting, theorizing, testing, archiving, ...) will involve understanding these information processes, and building systems that do the object-level science. Then the boundaries between the enterprise of science as a whole (the acquisition and organization of the knowledge of the world) and AI (the understanding of how knowledge is acquired and organized) will become increasingly fuzzy.

The goals of this symposium are to examine how far we have come to realizing Newell's vision, to identify fruitful current opportunities, and to discuss the obstacles to progress in further understanding of systematic methods for scientific inference. We solicit contributions that advance these goals. Some examples of appropriate contributions include:

A program that automates a complex and creative scientific task.
A new systematic method of scientific inference, even if its automation is not yet feasible.
A new representation or classification of science that enhances efforts to systematize it.
New opportunities for known systematic methods.
A recent scientific achievement where the computer played an essential creative role.
New heuristics for scientific research, e.g., that promise to make practicable some aspect of automated scientific reasoning.
Computational models of historical discoveries in science.
Cognitive studies of the scientific process that promise to contribute to computational approaches.

Contributions that potentially bear on more than one scientific area and that are demonstrably effective are of special interest.

SUBMISSION INFORMATION

Prospective participants are invited to submit (in paper form) one of the following to the symposium chair by October 28, 1994: three copies of an extended abstract (at most 5 pages) of work to be presented, a description of research in progress, or a statement describing what you hope to contribute to and gain from the symposium.

ORGANIZING COMMITTEE

Lindley Darden (Maryland), Joshua Lederberg (Rockefeller), Herbert Simon (Carnegie Mellon), Derek Sleeman (Aberdeen), Raul Valdes-Perez (chair, Carnegie Mellon)

Please send submissions and information requests to the symposium chairman as follows:

Raul Valdes-Perez, Computer Science Department, Carnegie Mellon University, Pittsburgh, PA 15213 - USA

(email: valdes@cs.cmu.edu)