Master's thesis of Engineering: Robust sensory systems for dynamic environments

In this thesis, focus on the wireless links between devices equipped by deployed operating personnel and intermediary access point infrastructure. We use multi-radio (MR) platforms, wireless devices with multiple and diverse transceiver technologies, to produce robust and reliable links through adaptive control of available transceivers. Primarily, we study the application of intelligent control techniques, namely reinforcement learning (RL), for adaptive control over diverse transceivers to achieve the desired robustness and reliability under dynamic environmental conditions.