Cog366 / Csc366 "Computational Models of Cognitive Processes"
Course Syllabus for Spring 2004
Instructor: Craig Graci
Text: None
Office: 114 Snygg Hall
Telephone: 315.312.2690
Course Description
Cognitive Science is a contemporary approach to the study of the mind. This course will paint a picture of Cognitive Science which features computational models of cognitive processes. More specifically, this course is an introduction to the computational study of human and machine intelligence. Discussion of symbolic computation, neural networking, and genetic computation. Examination of research in language, vision, perception, memory, learning, reasoning, planning, and information processing. Programming in LISP (CLOS) is a featured part of this course. An introduction to the language is integrated into tightly specified programming projects which, upon completion, constitute tools for investigating aspects of cognition from the symbolic, neural, and genetic perspectives.
Main Course Objectives
Upon successful completion of this course students will be able to:
- Describe the nature of the field, its fundamental goals and methodologies
- Describe the computational, representational, and interdisciplinary assumptions underlying the field.
- Describe aspects of cognition, computation, neuroscience, and evolution which possess a high degree of relevance to Cognitve Science.
- Explain the nature of symbol systems and engage in symbolic computation.
- Program the fundamental knowledge-representations of Artificial Intelligence which have become central to Cognitve Science.
- Describe the components, architectures, and algorithms associated with artificial neural networks. Explain the possible contributions of artificial neural networks to cognitive science.
- Suggest the significance of such issues as embedded cognition and emergent phenomena.
- Explain basic concepts associated with "Alife".
- Describe evolutionary programming from an algorithmic perspecitive.
- Summarize memetics, the application of evolutionary biological ideas to the study of the mind.
- Discuss research in machine learning and problem solving as it pertains to the investigation of these processes in humans.
- Discuss issues of knowledge acquisition, representation, and deployment within the realms of language, vision and music.
- Engage in modest researches of various cognitive scientific sorts.
Requirements
You are required to regularly attend class. You will be required to do homework in the form of readings and exercises. You are required to take all exams. Beyond this, you are required to render the contents of the course, lecture notes, handouts, assignments, exams, etc., in form of either a notebook or a Web site.
Grading
Your grade will be determined on the basis of:
- 3 exams (100 points each)
- 1 final exam (150 points)
- course notebook or course website (150 points)
- assignments (150 points)
Other Things
- Unless otherwise specified, all assignments for which submission is required must be handed in to me immediately after class in the room where this class regularly meets. All assignments must be presented in the form of an 8.5 x 11 inch document, bound on the left by three staples. Each must begin with a title page which includes your name, the number of the assignment, and a brief description of the assighment.
- Requests to make up exams or assignments will rarely be considered unless accompanied by a written medical excuse for your absense.
- It is intended that you complete your work by yourself. You are, of course, welcome to ask specific technical questions of others and converse over conceptual issues, but you should be doing your own work. Compelling evidence that someone other than you contributed conspicuously to the completion of required work will result in a "maximum negative" grade for that assignment, failure in the course, or worse.
- I don't correspond with students via email about matters pertaining to this course.