Many real-world applications for sensor networks require event sampling with sufficient resolution over both spatial and temporal dimensions. When the deployed nodes are insuffi...
Reinforcement learning problems are commonly tackled with temporal difference methods, which attempt to estimate the agent's optimal value function. In most real-world proble...
In this paper, we extend the classical result by Huang, Kintala, Kolettis and Fulton (1995), and in addition propose a modified stochastic model to determine the software rejuvena...
—WiFi localization and tracking of indoor moving objects is an important problem in many contexts of ubiquitous buildings, first responder environments, and others. Previous app...
This paper investigates hindsight optimization as an approach for leveraging the significant advances in deterministic planning for action selection in probabilistic domains. Hind...
Sung Wook Yoon, Alan Fern, Robert Givan, Subbarao ...