Adaptive scheduling in mobile ad hoc networks using reinforcement learning approach

This paper presents an adaptive scheduling scheme for quality of service (QoS) provisioning in wireless ad hoc networks. Our proposed scheme models the environment as a Markov Decision Process and uses a reinforcement learning technique that considers, in occurrence of collisions, maximizing the throughput and minimizing the average transmission energy in a wireless environment, by taking into account the channel conditions.