This paper introduces a novel method of adding intrinsic bonuses to task-oriented reward function in order efficiently facilitate reinforcement learning search. While various have been designed date, they are analogous the depth-first and breadth-first search algorithms graph theory. paper, therefore, first designs two for each them. Then, heuristic gain scheduling is applied bonuses, inspired ...

This paper deals with the problem of sampled-data gain-scheduling control design for affine quasi-LPV systems. As implementation is based on sample-data and its update occurs only at specific sampling instants, state-dependent scheduling functions controller are piecewise continuous. characteristic causes a mismatch between system model parameters, namely asynchronous respect to plant during in...