Fall, 2004
Instructors:
Brian Williams
&
Nick Roy
Monday and Wednesday
9:00am-10:30am 16.413
10:30am-12:00pm
16.410
Room: 33-418
Lectures | Announcements
| Project
| Handouts
This course surveys
a variety of reasoning, optimization, and decision-making methodologies for
creating highly autonomous systems and decision support aids. The focus is
on principles, algorithms, and their applications, taken from the disciplines
of artificial intelligence and operations research. Reasoning paradigms include
logic and deduction, heuristic and constraint-based search, model-based reasoning,
planning and execution, reasoning under uncertainty, and machine learning.
Optimization paradigms include linear and integer programming, dynamic programming,
and network optimization. Decision-making paradigms include decision analysis,
decision theoretic planning, and Markov decision processes.
For the Learning
Objectives, please click here.
For the Course Logistics, please click here.
Prerequisites: 6.041
and 16.070
* The course textbook is Artificial Intelligence: A Modern Approach,
2nd Edition, by Stuart Russell and Peter Norvig. You may purchase this at the Coop. This book
is on reserve at Barker Engineering Library.
* A
recommended textbook is Introduction to Operations Research, by Frederick S.
Hillier and Gerald J. Lieberman. You may purchase this at the Coop. This book
is on reserve at Barker Engineering Library.
***REGISTER FOR THE
ONLINE TUTORIAL
HERE***
Once you have registered,
you can access the tutorial
here.
Course
Staff:
Instructors:
» Brian Williams,
Rm 33-330, x3-1678 or 32-273, x3-2739