Catalog Description:
This course will introduce students to cognitive science by examining the integration of artificial intelligence, cognitive psychology, and the philosophy of mind and language in the development of a computational model for cognition. Issues to be addressed include symbolic and connectionist artificial intelligence, the nature of mental representation, problem solving, computational theory, and natural language processing.
Prerequisites:
Math 111 or equivalent. Some experience in programming will be helpful but is not required. Two Natural World core courses are required to be completed in advance for this course to count for an SCXT core course.
Explanation of prerequisites:
Math 111 (or equivalent) is needed for a general familiarity with algebraic expressions, linear and quadratic equations, and basic graphing (lines and simple linear inequalities). Specifically, it is used during discussions of neural networks.
The student will be introduced to the basics of programming in LISP and then some basic programming in CLIPS.
Learning objectives:
We have been asking about the nature of intelligence and the nature of consciousness since we started asking questions about ourselves and the world around us. With the advent of the computer, we have started asking a much more narrow question: Is intelligence, is consciousness, computational in nature?
This is the basic question (and the basic assumption) of cognitive science. This course will not answer that question. We don't have a convincing answer for it yet. What we will do during the course of this semester will be to examine this question, to learn more about it, so that whatever answer we find ourselves inclining to, we will be better informed.
There are some specific objectives for this semester (in addition to the more general ones outlined above):
- The student will gain an introductory understanding of what it means to say that intelligence is computational (a full understanding of that statement is, I believe, the basis for a full and satisfying career). To this end, the student will
- Acquire an understanding of what an algorithm is and learn how to implement small algorithms in the programming language LISP
- Develop an introductory understanding of formal models for computation, the limits of computation, the Chomsky hierarchy, and the Turing-Church hypothesis
- The student will study some of the modern attempts to demonstrate a computational model for intelligence through an introduction to the discipline of artificial intelligence, including introductions to knowledge representation, search, and artificial neural networks.
- The student will explore some of the positions taken in the ongoing discussion of this issue. We will look at what the data from Psychology tells us. In Philosophy and Linguistics, we will begin with Descartes, and look (and discuss) Turing, Gelernter, Newell and Simon, Penrose, Searle, and others, finishing with a partial response to Descartes given to us by Chomsky and others.
- Finally, as a capstone issue, students will be introduced to some of the basic ideas of computational linguistics as one of the important "test cases" for this approach to cognitive science.
The student should know that the instructor has no definite answers to the questions posed in this course, though he does have some opinions he is happy to share (which students should not feel in any way obliged to agree with). The instructor recognizes that there are good and thoughtful people (including several smarter than he is) who take contrary positions. Much of the effort of the course, then, will to be to develop an understanding of these issues sufficient to inform the student's future deliberation on them.
This is, I believe, one of the great questions of our time, and one which is unlikely to be answered soon. But it is great fun to explore and to discuss, so let us begin.
The course is in roughly six parts: