Participants read and evaluate papers from the current research literature, experiment with simulations of connectionist networks, and engage in semester-long research projects applying the connectionist approach to selected problems in machine learning, artificial intelligence, psychology, neurobiology, or linguistics. Topics in Symbolic Artificial Intelligence. Topics vary from year to year. Highly recommended prereq. Topics in Nonsymbolic Artificial Intelligence.
Topics vary from year to year.
Possible topics include human and machine vision, signal and speech processing, artificial life, mathematical foundations of connectionism, and computational learning theory. Readings and Research in Cognitive Science. Interdisciplinary reading of innovative theories and methodologies of cognitive science. Topics in Cognitive Science. Addresses different set of one to three topics each year.