In reinforcement learning, least-squares temporal difference methods (e.g., LSTD and LSPI) are effective, data-efficient techniques for policy evaluation and control with linear v...
Michael H. Bowling, Alborz Geramifard, David Winga...
Selecting an optimum maintenance policy independent of other parameters of the production system does not always yield the overall optimum operating conditions. For instance, high...
We consider the classical finite-state discounted Markovian decision problem, and we introduce a new policy iteration-like algorithm for finding the optimal state costs or Q-facto...
Despite several research studies, the effective analysis of policy based systems remains a significant challenge. Policy analysis should at least (i) be expressive (ii) take accou...
Robert Craven, Jorge Lobo, Jiefei Ma, Alessandra R...
Administrative RBAC (ARBAC) policies specify how Role-Based Access Control (RBAC) policies may be changed by each administrator. It is often difficult to fully understand the effe...
Scott D. Stoller, Ping Yang, C. R. Ramakrishnan, M...