MPhil Thesis Defence


"Sensor-Based Multiple-Goal Recognition"

By

Mr. Xiaoyong Chai


Abstract

Inferring a user's high-level goals from low-level sensor readings has
been drawing increasing attention from both AI and Pervasive Computing
communities recently. A common assumption made by most approaches is that
a user has a single goal in mind or aims to achieve several goals
sequentially. However, in real-world environments, a user often has
multiple goals concurrently carried out and a single action can serve as a
step towards multiple goals.

In this thesis, we formulate the sensor-based multiple-goal recognition
problem and exemplify it in an indoor environment where an RF-based
wireless network is available. We propose a recognition algorithm to infer
a user's multiple high-level goals from low-level sensory data. In our
approach, we establish a model set where goal recognition models are
instantiated and terminated dynamically. Each model is a finite state
machine and evolves over time among pre-defined states to perform
recognition. By distinguishing the state of a model, we can infer whether
one of a user's goal is present or not. Experiments with real data
demonstrated that our method can accurately and efficiently recognize
multiple goals in a user's trace. Thus, we provide a general framework for
goal recognition and achieve a major advance over previous work.


Date:				Thursday, 23 June 2005

Time:				3:00p.m.-5:00p.m.

Venue:				Room 1504
				Lifts 25-26

Committee Members:		Dr. Qiang Yang (Supervisor)
                        	Dr. Dit-Yan Yeung (Chairperson)
                        	Dr. James Kwok


**** ALL are Welcome ****