Learning from experimentation allows a system to acquire planning domain knowledge by correcting its knowledge when an action execution fails. Experiments are designed and planned...
This paper presents a semantic space profiler for parallel functional programs. Building on previous work in sequential profiling, our tools help programmers to relate runtime res...
Daniel Spoonhower, Guy E. Blelloch, Robert Harper,...
— Reinforcement Learning (RL) provides a promising new approach to systems performance management that differs radically from standard queuing-theoretic approaches making use of ...
Gerald Tesauro, Nicholas K. Jong, Rajarshi Das, Mo...
Simulating a system of agents that navigate in a physical space is a challenging problem when the environment is sophisticated and the number of agents involved is large. We descr...
Despite decades of research in extensible operating system technology, extensions such as device drivers remain a significant cause of system failures. In Windows XP, for example,...