We present a new approach for estimation and optimization of the average stand-by power dissipation in large MOS digital circuits. To overcome the complexity of state dependence i...
Supamas Sirichotiyakul, Tim Edwards, Chanhee Oh, J...
Partially observable Markov decision processes (POMDPs) provide a principled, general framework for robot motion planning in uncertain and dynamic environments. They have been app...
Sylvie C. W. Ong, Shao Wei Png, David Hsu, Wee Sun...
User-session-based testing of web applications gathers user sessions to create and continually update test suites based on real user input in the field. To support this approach ...
Sara Sprenkle, Emily Gibson, Sreedevi Sampath, Lor...
Complex and long-lived software need to be upgraded at runtime. Replacing a software component with a newer version is the basic evolution operation that has to be supported. It i...
We consider reinforcement learning in the parameterized setup, where the model is known to belong to a parameterized family of Markov Decision Processes (MDPs). We further impose ...