Application of State Space Search Algorithms to Optimal Control

State space search is usually used in the field of artificial intelligence, in which successive states of an instance are considered, with the goal of finding a path to some desired state. Many different searching algorithms were also developed for the connected graphs or trees traversing [1-3]. Application of such algorithms to continuous state-space is somewhat difficult since it leads to the potentially infinite number of possible states after space partitioning on one hand, or loss of the accuracy on the other. At the same time solving optimal control problems with the existing algorithms often considered to be impractical due to the exponential growth of the states to be analysed. This paper addresses the mentioned above problems as well as other important aspects of solving the optimal control problems.