Large-scale probabilistic knowledge bases are becoming increasingly important in academia and industry. They continuously extended with new data, powered by modern information extraction tools that associate probabilities base facts. The state of the art to store process such data is founded on databases. Many systems based databases, however, still have certain semantic deficiencies, which lim...

Over the past few decades great efforts were made to solve uncertain hybrid optimization problems. The n-Queen problem is one of such problems that many solutions have been proposed for. The traditional methods to solve this problem are exponential in terms of runtime and are not acceptable in terms of space and memory complexity. In this study, parallel genetic algorithms are proposed to solve...

using the usual definitions of information and entropy in quantum gravity and statistical mechanics and the existing views about the relation between information and complexity, we examine the evolution of complexity in an ever expanding universe.

being one of the major research fields in the robotics discipline, the robot motion planning problem deals with finding an obstacle-free start-to-goal path for a robot navigating among workspace obstacles. such a problem is also encountered in path planning of intelligent vehicles and automatic guided vehicles (agvs). traditional (exact) algorithms have failed to solve the problem effectively s...