Ontologies and Knowledge Representation
3.0
creditsAverage Course Rating
Knowledge representation (KR) deals with the possible structures by which the content of what is known can be formally represented in such a way that queries can be posed and inferences drawn. Ontology concerns the hierarchi- cal classification of entities from given domains of knowledge together with the relations between various classes or subclasses. We begin with KR, examining the standard variety of frameworks developed or implemented over the last twenty years, including 1st-order logic and automated theorem proving, networks, frames, and description logics. Then we move on to a study of the problems inherent in ontology development and examine the some of the currently prevalent environments, including Universal Modeling Language, OWL and Protege', RDFS and semantic web applications. [Analysis] Recommended Course Background: EN.600.107
Spring 2014
Professor: Robert Rynasiewicz
The best aspects of this course were the interesting topics covered, the very cool software, and the introduction to kinematics. The class is about robotics, which is pretty cool regardless of the format. The worst aspects of the course was the disconnect between the theoretical lectures and the practical homework. Many students thought this led to overly complicated homework. Some suggestions for improvement included more exam review sessions, more interaction in class, and more instruction in RoS. Prospective students should have a strong programming and linear algebra background. The class is interesting and fun, but a good deal of work.