In this paper, we investigate the use of parallelization in reinforcement learning (RL), with the goal of learning optimal policies for single-agent RL problems more quickly by us...
We have developed a distributed DSS capable to working in a dynamic way. That is, when a domain of an organization needs a new kind of information, the system looks for this infor...
Abstract. The navigation task is a very demanding application for mobile users. The algorithms of present software solutions are based on the established methods of car navigation ...
Today, systems should react based on explicit demands from the learner or even proactively react based on changes in the working environment. The success of this type of systems de...
In software development, many kinds of knowledge are shared and reused as software patterns. Howevel; the relation analysis among software by hand is on the large scale. In this w...