Goal-oriented policies for cost of actuation error minimization in wireless autonomous systems

We consider the minimization of the cost of actuation error under resource constraints for real-time tracking in wireless autonomous systems. A transmitter monitors the state of a discrete random process and sends updates to a receiver over an unreliable wireless channel. The receiver then take s actions according to the estimated state of the source. For each discrepancy between the real state of the source and the estimated one, we consider a different cost of actuation error. This models the case where some states, and consequently the corresponding actions to be taken, are more important than others. We provide two algorithms, a first one reaching an optimal solution but o f high complexity, and a second low-complexity one that provides a suboptimal solution. Our simulation results evince that the performance of the two algorithms are quite close.