Exact number not yet decided
Graduate students with an interest in artificial intelligence and automated planning.
The course was last given
Planning is the task of thinking before you act: Not only reacting to the environment, but using knowledge about the world to determine what to do in order to achieve a given goal. Automated planning is a central topic in AI, and task and motion planning capabilities are essential to the construction of many robust autonomous systems. Recently, research in planning has seen a great deal of excitement, with a variety of new approaches vastly outperforming older techniques in terms of speed as well as applicability and expressive power. Planning technologies are currently used with great success in applications ranging from production lines and elevators to unmanned aerial vehicles (UAVs) and space applications such as the Hubble Space Telescope and the Mars rovers. The aim of this course is to provide a comprehensive view of a wide range of planning techniques, as well as hands-on experience in constructing and modeling planning domains to solve specific planning problems.
Basic knowledge and understanding of data structures and algorithms as well as discrete mathematics and (simple uses of) first-order logic.
* Introduction to planning
* The classical planning paradigm
* Algorithms for classical and neo-classical planning
* Planning with rich domain knowledge: How to make use of all you know
* Planning under uncertainty: How to handle incomplete knowledge
* Plan execution and monitoring: No plan survives contact with reality!
* A brief introduction to path planning and motion planning
A series of lectures present the theory behind planning as well as many practically useful techniques for plan generation under varying assumptions about the environment. A set of exercises provide hands-on experience using several state-of-the-art planning paradigms and planning systems.
Automated Planning: Theory and Practice, Malik Ghallab, Dana Nau and Paolo
Traverso, ISBN: 1-55860-856-7.
Lecture notes and possibly a couple of handouts.
Assignments and written exam.
(To be discussed -- might vary depending on the amount of work put in?)
Page responsible: Director of Graduate Studies
Last updated: 2012-05-03