Factored representations, model-based learning, and hierarchies are well-studied techniques for improving the learning efficiency of reinforcement-learning algorithms in large-sca...
Carlos Diuk, Alexander L. Strehl, Michael L. Littm...
This paper examines agent-based systems designed for a variety of human learning tasks. These are typically split into two areas: "training", which generally refers to a...
Bandwidth demands of communication networks are rising permanently. Thus, the requirements to modern routers regarding packet classification are rising accordingly. Conventional al...
The organization of objects into classes and categories is an essential task in the process of forming concepts. Within computer science, this classification activity must be suppo...
This paper presents a new worklist algorithm that significantly speeds up a large class of flow-sensitive data-flow analyses, including typestate error checking and pointer analysi...