Monitoring and control of anytime algorithms: A dynamic programming approach Export

@article{citeulike:2294437, abstract = {Anytime algorithms offer a tradeoff between solution quality and computation time that has proved useful in solving time-critical problems such as planning and scheduling, belief network evaluation, and information gathering. To exploit this tradeoff, a system must be able to decide when to stop deliberation and act on the currently available solution. This paper analyzes the characteristics of existing techniques for meta-level control of anytime algorithms and develops a new framework for monitoring and control. The new framework handles effectively the uncertainty associated with the algorithm's performance profile, the uncertainty associated with the domain of operation, and the cost of monitoring progress. The result is an efficient non-myopic solution to the meta-level control problem for anytime algorithms.}, author = {Hansen, Eric A. and Zilberstein, Shlomo}, citeulike-article-id = {2294437}, citeulike-linkout-0 = {http://dx.doi.org/10.1016/S0004-3702(00)00068-0}, citeulike-linkout-1 = {http://www.sciencedirect.com/science/article/B6TYF-42KDH2N-6/2/168626f24b584bca019b4153aa108f0b}, doi = {10.1016/S0004-3702(00)00068-0}, journal = {Artificial Intelligence}, keywords = {anytime\_algorithms, dynamic\_programming}, month = {February}, number = {1-2}, pages = {139--157}, posted-at = {2008-01-27 06:18:42}, priority = {2}, title = {Monitoring and control of anytime algorithms: A dynamic programming approach}, url = {http://dx.doi.org/10.1016/S0004-3702(00)00068-0}, volume = {126}, year = {2001} }

TY - JOUR ID - citeulike:2294437 L3 - citeulike-article-id:2294437 N2 - Anytime algorithms offer a tradeoff between solution quality and computation time that has proved useful in solving time-critical problems such as planning and scheduling, belief network evaluation, and information gathering. To exploit this tradeoff, a system must be able to decide when to stop deliberation and act on the currently available solution. This paper analyzes the characteristics of existing techniques for meta-level control of anytime algorithms and develops a new framework for monitoring and control. The new framework handles effectively the uncertainty associated with the algorithm's performance profile, the uncertainty associated with the domain of operation, and the cost of monitoring progress. The result is an efficient non-myopic solution to the meta-level control problem for anytime algorithms. IS - 1-2 JF - Artificial Intelligence EP - 157 TI - Monitoring and control of anytime algorithms: A dynamic programming approach VL - 126 SP - 139 KW - anytime_algorithms KW - dynamic_programming AU - Hansen, Eric AU - Zilberstein, Shlomo PY - 2001/02// UR - http://dx.doi.org/10.1016/S0004-3702(00)00068-0 ER -