In reinforcement learning, an agent interacting with its environment strives to learn a policy that specifies, for each state it may encounter, what action to take. Evolutionary c...
Software distributed shared memory (DSM) techniques, while effective on applications with coarse-grained sharing, yield poor performance for the fine-grained sharing encountered i...
We describe SCC-kS, a Speculative Concurrency Control (SCC) algorithm that allows a DBMS to use efficiently the extra computing resources available in the system to increase the l...
Over the last several years, a new probabilistic representation for 3-d volumetric modeling has been developed. The main purpose of the model is to detect deviations from the norm...
In this paper, the advantages of introducing an additional amount of tests when evolving parameters for specific purposes is discussed. A set of optimal PID-controller parameters...