Modeling and Prediction of Human Behavior

1 January 1999

journal article
Published by MIT Press in Neural Computation

Vol. 11 (1) , 229-242
https://doi.org/10.1162/089976699300016890

Abstract

We propose that many human behaviors can be accurately described as a set of dynamic models (e.g., Kalman filters) sequenced together by a Markov chain. We then use these dynamic Markov models to recognize human behaviors from sensory data and to predict human behaviors over a few seconds time. To test the power of this modeling approach, we report an experiment in which we were able to achieve 95% accuracy at predicting automobile drivers' subsequent actions from their initial preparatory movements.

Keywords

HUMAN BEHAVIOR

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