Computing Optimal Mixed Strategies for Security Games with Dynamic Payoffs
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence. Main Track. Pages 681-687.
Abstract
Security agencies in the real world often need to protect targets with time-dependent values, e.g., tourist sites where the number of travelers changes over time. Since the values of different targets often change asynchronously, the defender can relocate security resources among targets dynamically to make the best use of limited resources. We propose a game-theoretic scheme to develop dynamic, randomized security strategies in consideration of adversary's surveillance capability. This differs from previous studies on security games by considering varying target values and continuous strategy spaces of the security agency and the adversary. The main challenge lies in the computational intensiveness due to the continuous, hence infinite strategy spaces. We propose an optimal algorithm and an arbitrarily near-optimal algorithm to compute security strategies under different conditions. Experimental results show that both algorithms significantly outperform existing approaches.
@inproceedings{ijcai2015p102,
title = {Computing Optimal Mixed Strategies for Security Games with Dynamic Payoffs},
author = {Yin, Yue and Xu, Haifeng and Gan, Jiarui and An, Bo and Jiang, Albert Xin},
booktitle = {Proceedings of the Twenty-Fourth International Joint Conference on
Artificial Intelligence, {IJCAI-15}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Qiang Yang and Michael Wooldridge},
pages = {681--687},
year = {2015},
month = {7},
note = {Main Track},
url = {https://ijcai.org/proceedings/2015/102},
}
TY - CPAPER TI - Computing Optimal Mixed Strategies for Security Games with Dynamic Payoffs AU - Yin, Yue AU - Xu, Haifeng AU - Gan, Jiarui AU - An, Bo AU - Jiang, Albert Xin T2 - Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-15 PB - International Joint Conferences on Artificial Intelligence PY - 2015 SP - 681 EP - 687 UR - https://ijcai.org/proceedings/2015/102 ER -Copied
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