In environments where exact synchronization between source data objects and cached copies is not achievable due to bandwidth or other resource constraints, stale (out-of-date) cop...
Incomplete decision algorithms can often solve larger problem instances than complete ones. The drawback is that one does not know whether the algorithm will finish soon, later, ...
Reinforcement learning (RL) can be impractical for many high dimensional problems because of the computational cost of doing stochastic search in large state spaces. We propose a ...
We describe Bro, a stand-alone system for detecting network intruders in real-time by passively monitoring a network link over which the intruder's traffic transits. We give ...
— Reinforcement learning (RL) is one of the most general approaches to learning control. Its applicability to complex motor systems, however, has been largely impossible so far d...