Multi-class network is becoming a more attractive solution to provide Quality-of-Service guarantee, as more quality-demanding applications are emerging. This research considers ne...
In this paper, we present a general machine learning approach to the problem of deciding when to share probabilistic beliefs between agents for distributed monitoring. Our approac...
In this paper, an internal design model called FunState (functions driven by state machines) is presented that enables the representation of different types of system components a...
We study the problem of exploiting parallelism from search-based AI systems on distributed machines. We propose stack-splitting, a technique for implementing orparallelism, which ...
Approximate Linear Programming (ALP) is a reinforcement learning technique with nice theoretical properties, but it often performs poorly in practice. We identify some reasons for...