Temporal planning (TP) is notoriously difficult because it requires to solve a propositional STRIPS planning problem with temporal constraints. In this paper, we propose an efficie...
Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...
Abstract. We study the problem of dynamic load-balancing on hierarchical platforms. In particular, we consider applications involving heavy communications on a distributed platform...
Storage mapping optimization is a flexible approach to folding array dimensions in numerical codes. It is designed to reduce the memory footprint after a wide spectrum of loop tr...
SIMD organizations amortize the area and power of fetch, decode, and issue logic across multiple processing units in order to maximize throughput for a given area and power budget...