RRL is a relational reinforcement learning system based on Q-learning in relational state-action spaces. It aims to enable agents to learn how to act in an environment that has no ...
Many methods for XML processing have been proposed in the last few years. One popular approach is to process XML documents by using existing programming languages. Another popular...
Software synthesis for system level design languages becomes feasible because the current technology, pricing and application trends will most likely alleviate the industrial empha...
In this paper, an interactive system for the development of Image Processing applications is described. This system is intended to provide some assistance to Image Processing exper...
This paper presents a novel system architecture applicable to high-performance and flexible transport data processing which includes complex protocol operation and a network contr...