office hour: Thursday 2-3pm, 731 SODA or by appointment
With over 100 billion parallel computing elements, the brain's capacity
for encoding, communicating, and processing information is remarkable.
But the brain is also extremely limited: neurons are slow devices, their
computation appears relatively undifferentiated with respect to the needs
of symbolic computation, and they communicate via messages that encode
only a few bits of information. Despite these limitations, our brain is
adept at performing certain types of symbolic processing and learning tasks
with remarkable ease (e.g., learning and understanding language).
In this course we will study how biological systems can perform such an impressive
computational feats and how the resulting insights can be applied in engineering
as well as science. The standpoint will be computer science, but will employ
results and methods from several disciplines.
Prerequisite for the course is graduate standing in any field OR completion
of the course: CS188: Artificial Intelligence OR
permission of the instructors. The course will involve considerable use
of simulation packages and some math, but
programming will not be required. The required term project can, of course,
be programming intensive.