CS 7341. Conceptual Information Processing.
In-depth introduction to the conceptual approach to language, understanding,
inference and reasoning. Topics include knowledge representation, inference
and causality, conceptual analysis of natural language, story generation,
explanation, memory, learning and integrated processing.
Kolodner,
Eiselt,
Ram.
- Course title: CS 7341, Conceptual Information Processing
- Instructor: Prof. Ashwin Ram, College of Computing
- Quarter: Spring 1994
- Credit hours: 3-0-3
- Prerequisites: Introductory AI course or permission of instructor
- Description:
"Conceptual Information Processing" is a course designed to
give beginning to intermediate students an in-depth
introduction to the conceptual approach to understanding and reasoning. We
will cover topics such as knowledge representation (general issues in
knowledge representation as well as some specific knowledge representation
schemes such as conceptual dependency and semantic networks), inference and
causality, conceptual analysis of natural language text (understanding
sentences, understanding script-based stories, understanding goal-based
stories), controlling inferences (scripts, frames and other schemas),
explanation (explanatory coherence, explanation patterns, creative
explanation), learning (similarity-based learning, explanation-based
learning, goal-driven learning), memory (representation, memory
organization), and natural language story generation.
- Structure:
The intent of the course is to provide a background in
conceptual information processing, experience in thinking
creatively about issues in this area, and a feel for what doing research in
AI is all about. Classes to consist of active discussions in addition to
lectures; class participation will be important and encouraged. Class
lectures and discussions will be complemented by reading and programming
assignments.
- Audience:
The course is appropriate for anyone interested in conceptual
AI as a research area, and also for anyone interested in
applying conceptual AI techniques to other research or application areas. If
you know absolutely nothing about AI (specifically, if the terms "knowledge
representation" and "search" don't ring any bells), you probably want to take
CS6361 before taking this course, but if you've had an AI course before
and/or some experience with an AI project, you'll be ok. If you're unsure
about whether this course is right for you, talk to the instructor.
- For more info:
Contact Ashwin Ram, ashwin.ram@cc.gatech.edu, 853-9372, or swing
by my office (Room 114 CoC).