Optimal schedules for monitoring anytime algorithms

@article{Finkelstein2001Optimal, abstract = {Monitoring anytime algorithms can significantly improve their performance. This work deals with the problem of off-line construction of monitoring schedules. We study a model where queries are submitted to the monitored process in order to detect satisfaction of a given goal predicate. The queries consume time from the monitored process, thus delaying the time of satisfying the goal condition. We present a formal model for this class of problems and provide a theoretical analysis of the class...}, author = {Finkelstein, Lev and Markovitch, Shaul }, citeulike-article-id = {1439684}, journal = {Artificial Intelligence}, keywords = {anytime-algorithms}, number = {1-2}, pages = {63--108}, posted-at = {2007-07-06 16:55:42}, priority = {0}, title = {Optimal schedules for monitoring anytime algorithms}, url = {http://citeseer.ist.psu.edu/528444.html}, volume = {126}, year = {2001} }

TY - JOUR ID - Finkelstein2001Optimal L3 - citeulike-article-id:1439684 TI - Optimal schedules for monitoring anytime algorithms JF - Artificial Intelligence VL - 126 IS - 1-2 SP - 63 EP - 108 N2 - Monitoring anytime algorithms can significantly improve their performance. This work deals with the problem of off-line construction of monitoring schedules. We study a model where queries are submitted to the monitored process in order to detect satisfaction of a given goal predicate. The queries consume time from the monitored process, thus delaying the time of satisfying the goal condition. We present a formal model for this class of problems and provide a theoretical analysis of the class... KW - anytime-algorithms AU - Finkelstein, Lev AU - Markovitch, Shaul PY - 2001/// UR - http://citeseer.ist.psu.edu/528444.html ER -