16.410 / 16.413 Principles of Autonomy and Decision Making

Fall 2005

An artist's rendering of the Mars rover.
Artist's rendering of Mars Exploration Rover. (Image courtesy of NASA/JPL-Caltech.)

Course Highlights

This course features a complete set of lecture notes as well as the assignments and practice exams.

Course Description

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, integer and dynamic programming. Decision-making paradigms include decision theoretic planning, and Markov decision processes. This course is offered both to undergraduate (16.410) students as a professional area undergraduate subject, in the field of aerospace information technology, and graduate (16.413) students.

Technical Requirements

Special software is required to use some of the files in this course: .java.

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Staff

Instructors:
Prof. Brian Williams
Prof. Nicholas Roy

Course Meeting Times

Lectures:
Two sessions / week
1.5 hours / session

Level

Undergraduate / Graduate

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