Multiple-goal recognition from low-level signals

  • Authors:

  • Xiaoyong Chai;Qiang Yang

  • Affiliations:

  • Department of Computer Science, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China;Department of Computer Science, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China

  • Venue:
  • AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
  • Year:
  • 2005

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Abstract

Researchers and practitioners from both the artificial intelligence and pervasive computing communities have been paying increasing attention to the task of inferring users' high-level goals from low-level sensor readings. A common assumption made by most approaches is that a user either has a single goal in mind, or achieves several goals sequentially. However, in real-world environments, a user often has multiple goals that are concurrently carried out, and a single action can serve as a common step towards multiple goals. In this paper, we formulate the multiple-goal recognition problem and exemplify it in an indoor environment where an RF-based wireless network is available. We propose a goal-recognition algorithm based on a dynamic model set and show how goal models evolve over time based on pre-defined states. Experiments with real data demonstrate that our method can accurately and efficiently recognize multiple interleaving goals in a user's trace.