Student research opportunities
Mars Rovers and Traffic Controllers
Project Code: CECS_46
This project is available at the following levels:
Honours, Summer Scholar, Masters, PhD
Supervisor:
Dr Scott SannerOutline:
Markov decision processes (MDPs) are a theoretical tool for modeling sequential decision making problems and their optimal solution. Recent advances in the theory of MDPs permit efficient solutions to problems with both continuous state and action spaces. Such models are highly appropriate for planning in both Mars Rovers and Traffic Controllers (just to name two examples).
Goals of this project
In this project, you would choose one of these problem domains (or perhaps another you can suggest) and implement an (approximately) optimal planning system for this task. This project offers the chance for the student to learn about the theory of optimal sequential decision making and its application to practical problems.
Background Literature
A nice introduction to MDPs is given in Chapters 1-4 of "Reinforcement Learning", Rich Sutton and Andy Barto (1998).
Links
Scott Sanner's web pageBackground reading available online
