John H Gennari
A readings class in knowledge representation, as described in the primary artificial intelligence and biomedical informatics literature. Topics may include: frame-based systems, description logics, theorem proving, complexity vs. tractability, ontologies, rule-based systems, and biomedical domain applications. Prerequisite: any artificial intelligence course (e.g., CSE 415 or better), or permission of instructor.
(1) Gain at least a familiarity with some basic KR formalisms: (a) FOL, (b) Rules, (c) Semantic nets, and (d) Frames. (2) Understand inference and the implications for tractable KR systems. (3) Have a knowledge-level understanding of some biomedical and health applications that rely on KR. (4) Be able to critically read and review primary literature about KR. This includes the ability to create synthetic written reviews that connect ideas across multiple readings.
I will lead this course in two modes: Primarily in a seminar fashion, where we discuss a particular paper or set of papers. Secondarily, I will have some didactic material that covers particular methods or formalisms. At all times student participation is expected and encouraged.
Although I have listed an AI course as a prerequisite, my main request is that students have some preparation with formal, abstract thinking. In particular, familiarity with logic some of the mathematical theory of computer science is what I would like students to know prior to taking this course.
Class Assignments and Grading
There may be one or two exercises to demonstrate familiarity with notation or methods, but most homeworks will be writing assignments: 2-page "reaction paper" assignments in response to selected readings. There will also be a final project.
This course will be evaluated on the basis of formal writing assignments, class participation, and on a final project.