: Decision-support systems that help solving problems in open and weak theory domains, i.e. hard problems, need improved methods to ground their models in real world situations. Mo...
Large scale distributed systems typically have interactions among different services that create an avenue for propagation of a failure from one service to another. The failures ...
In some real world situations, linear models are not sufficient to represent accurately complex relations between input variables and output variables of a studied system. Multila...
Robots that can adapt and perform multiple tasks promise to be a powerful tool with many applications. In order to achieve such robots, control systems have to be constructed that...
Real-time control has become increasingly important as technologies are moved from the lab into real world situations. The complexity associated with these systems increases as co...
The current framework of reinforcement learning is based on maximizing the expected returns based on scalar rewards. But in many real world situations, tradeoffs must be made amon...