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...

In this paper we study the fundamental scheduling, multiplexing and diversity trade-off in MIMO ad hoc networks. In particular, we propose a unified framework for the schedulingmultiplexing and scheduling-diversity sub-problems that constitutes a major step towards solving the overall problem. The two sub-problems are motivated by a fundamental trade-off between scheduling full multiplexing (di...