AIC Seminar Series

A map is a key component for a mobile robot or general AI agent. Maps at their core allow an agent to answer three questions: (1) "where have I been?" (2) "where am I now?" and (3) "how do I get where I want to go?" A huge part of AI/robotics research assumes their existence, and another large body of research tries to build them. But building maps is time-consuming, manually intensive, and requires expert knowledge in the form of detailed models of the agent's motion and sensor apparatus. In this talk I will show how maps can be learned directly from an agent's own subjective experience of sensations and actions, without any models. I'll introduce a new algorithm, Action Respecting Embedding (ARE), inspired by kernel-based dimensionality reduction techniques. ARE extracts a low dimensional representation of data that also respects the provided action labelling. The resulting subjective map explicitly encodes the robot's trajectory (answering question one), and I'll show how it can be used for both planning (question three) and localization (question two). I'll then discuss some recent developments toward scaling this technique to interesting sized data sets.

Michael Bowling is an associate professor at the University of Alberta. He received his Ph.D. in 2003 from Carnegie Mellon University in the area of artificial intelligence. His research focuses on machine learning and robotics, and he is particularly fascinated by the problem of how computers can learn to play games through experience. He has participated extensively in the RoboCup initiative, an international, autonomous, robot soccer competition. In 1998, he was the leader of the Carnegie Mellon small-size robot team, which won the RoboCup world championship. More recently, as leader of the Computer Poker Research Group at the University of Alberta, he has helped build some of the world's strongest poker playing programs. The programs have won international "bot" competitions, as well as giving professional players stiff competition in the First Man-Machine Poker Championship, which took place this past July.

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