EECS 692: Special Topics in AI: Robot Learning

Course Description

Intelligent robots are becoming ever more present in our lives (think of the Google self-driving car) and ever more sophisticated. But we still face a huge challenge of creating robots that can function effectively, robustly, and safely in the complexity of the everyday human environment. Learning will be necessary to meet this challenge, but precisely what to learn, and how to represent what is learned, remain substantial challenges.

Fortunately, we have examples of intelligent creatures that learn sophisticated knowledge about complex environments: human infants and children. Insights from developmental psychology have inspired advances in knowledge representation, computer vision, and robot learning.

Previous work on representation and learning of knowledge about space, objects, actions, and so on, has largely focused on learning from autonomous experience, without concern for other agents. In this research seminar, we will draw on that foundation to investigate robot learning in domains that explicitly involve other agents. We will focus on three major themes.

Since we will be drawing on insights from multiple researchers with different perspectives, it is important for anyone working in this area to remember the important lesson of The Blind Men and the Elephant. We will gather clues where we can, to infer what our "elephant" looks like.

There will be many assigned readings from the research literature. Students will make presentations and lead discussions on state-of-the-art research, and will do a substantial term project culminating in a publication-quality paper. Within this problem area, each student will select the specific topic and methods for their term project to fit their own background and expertise.