EFFICIENT LINEAR APPROXIMATIONS TO STOCHASTIC VEHICULAR COLLISION-AVOIDANCE PROBLEMS
Dmitri Dolgov, Ken Laberteaux
2005
Abstract
The key components of an intelligent vehicular collision-avoidance system are sensing, evaluation, and decision making. We focus on the latter task of finding (approximately) optimal collision-avoidance control policies, a problem naturally modeled as a Markov decision process. However, standard MDP models scale exponentially with the number of state features, rendering them inept for large-scale domains. To address this, factored MDP representations and approximation methods have been proposed. We approximate collisionavoidance factored MDP using a composite approximate linear programming approach that symmetrically approximates objective functions and feasible regions of the LP. We show empirically that, combined with a novel basis-selection method, this produces high-quality approximations at very low computational cost.
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in Harvard Style
Dolgov D. and Laberteaux K. (2005). EFFICIENT LINEAR APPROXIMATIONS TO STOCHASTIC VEHICULAR COLLISION-AVOIDANCE PROBLEMS . In Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 972-8865-29-5, pages 275-278. DOI: 10.5220/0001162002750278
in Bibtex Style
@conference{icinco05,
author={Dmitri Dolgov and Ken Laberteaux},
title={EFFICIENT LINEAR APPROXIMATIONS TO STOCHASTIC VEHICULAR COLLISION-AVOIDANCE PROBLEMS},
booktitle={Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2005},
pages={275-278},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001162002750278},
isbn={972-8865-29-5},
}
in EndNote Style
TY - CONF
JO - Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - EFFICIENT LINEAR APPROXIMATIONS TO STOCHASTIC VEHICULAR COLLISION-AVOIDANCE PROBLEMS
SN - 972-8865-29-5
AU - Dolgov D.
AU - Laberteaux K.
PY - 2005
SP - 275
EP - 278
DO - 10.5220/0001162002750278