Consider a scenario where one desires to simulate the execution of some graph algorithm on random input graphs of huge, perhaps even exponential size. Sampling and storing these h...
Temporal difference reinforcement learning algorithms are perfectly suited to autonomous agents because they learn directly from an agent’s experience based on sequential actio...
In this paper we experimentally analyse various dynamic timeout adjustment strategies in server queues as potential counter-measures against degradation of service attacks. Previo...
Schulenburg [15] first proposed the idea to model different trader types by supplying different input information sets to a group of homogenous LCS agent. Gershoff [12] investigat...
In a dynamic reordering superscalar processor, the front-end fetches instructions and places them in the issue queue. Instructions are then issued by the back-end execution core. T...