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Behavior modeling using a hierarchical HMM approach

Chiao, S.-Y. and Xydeas, C.S. (2004) Behavior modeling using a hierarchical HMM approach. In: Hybrid Intelligent Systems, 2004. HIS '04. Fourth International Conference on. IEEE, pp. 92-97. ISBN 0-7695-2291-2

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Abstract

We introduce a new methodology for the hierarchical modeling of the behavior-with-time of players operating and interacting within a certain application domain. Behavior modelling and characterization are performed online, given that a number of observations are made or sensed at regular time intervals with respect to each player. A key element of this hierarchical behavior modeling system architecture is a new formulation of multiple hidden Markov models (HMM) with discrete densities operating in parallel, with each HMM accepting a single feature-related observation sequence. However the proposed classification approach recognizes the existence of possible dependencies between the observation sequences of the features obtained for a given player. This property is effectively exploited in a new dependent-multiHMM with discrete densities (DM-HMM-D) classification approach. The proposed methodology is applied in modeling the behavior of aircrafts operating in relatively simple 3D "air-patrol" situations. Computer simulation results demonstrate the significant gains that can be obtained in system classification and modeling performance when compared to those obtained while using conventional independent-multidiscrete hidden Markov model (IM-HMM-D) schemes.

Item Type: Contribution in Book/Report/Proceedings
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments: Faculty of Science and Technology > School of Computing & Communications
ID Code: 57496
Deposited By: ep_importer_pure
Deposited On: 12 Oct 2012 13:41
Refereed?: No
Published?: Published
Last Modified: 10 Apr 2014 01:25
Identification Number:
URI: http://eprints.lancs.ac.uk/id/eprint/57496

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