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...
Reinforcement learning problems are commonly tackled with temporal difference methods, which attempt to estimate the agent's optimal value function. In most real-world proble...
Cognitive architectures aspire for generality both in terms of problem solving and learning across a range of problems, yet to date few examples of domain independent learning has...
Systems software for clusters typically derives from a multiplicity of sources: the kernel itself, software associated with a particular distribution, site-specific purchased or o...
Ewing L. Lusk, Narayan Desai, Rick Bradshaw, Andre...
The objective of dynamic voltage scaling (DVS) is to adapt the frequency and voltage for configurable platforms to obtain energy savings. DVS is especially attractive for video dec...