Principles of Autonomy and Decision Making

Image combining data taken by an autonomous vehicle with the views from its windows.

The planning algorithm of Talos, the MIT entry to the DARPA Urban Challenge, in action. See Lecture 15 for more information. (Image by Emilio Frazzoli.)

Instructor(s)

MIT Course Number

16.410 / 16.413

As Taught In

Fall 2010

Level

Undergraduate

Cite This Course

Course Description

Course Features

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 application, 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, and machine learning. Optimization paradigms include linear programming, integer programming, and dynamic programming. Decision-making paradigms include decision theoretic planning, and Markov decision processes.

Other Versions

Related Content

Brian Williams, and Emilio Frazzoli. 16.410 Principles of Autonomy and Decision Making. Fall 2010. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu. License: Creative Commons BY-NC-SA.


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