--- res: bibo_abstract: - 'In this work we use autonomous vehicles to improve the performance of Wireless Sensor Networks (WSNs). In contrast to other autonomous vehicle applications, WSNs have two metrics for performance evaluation. First, quality of information (QoI) which is used to measure the quality of sensed data (e.g., measurement uncertainties or signal strength). Second, quality of service (QoS) which is used to measure the network''s performance for data forwarding (e.g., delay and packet losses). As a use case, we consider wireless acoustic sensor networks, where a group of speakers move inside a room and there are autonomous vehicles installed with microphones for streaming the audio data. We formulate the problem as a Markov decision problem (MDP) and solve it using Deep-Q-Networks (DQN). Additionally, we compare the performance of DQN solution to two different real-world implementations: speakers holding/passing microphones and microphones being preinstalled in fixed positions. We show that the performance of autonomous vehicles in terms of QoI and QoS is better than the real-world implementation in some scenarios. Moreover, we study the impact of the vehicles speed on the learning process of the DQN solution and show how low speeds degrade the performance. Finally, we compare the DQN solution to a heuristic one and provide theoretical analysis of the performance with respect to dynamic WSNs.@eng' bibo_authorlist: - foaf_Person: foaf_givenName: Haitham foaf_name: Afifi, Haitham foaf_surname: Afifi foaf_workInfoHomepage: http://www.librecat.org/personId=65718 - foaf_Person: foaf_givenName: Arunselvan foaf_name: Ramaswamy, Arunselvan foaf_surname: Ramaswamy foaf_workInfoHomepage: http://www.librecat.org/personId=66937 orcid: https://orcid.org/ 0000-0001-7547-8111 - foaf_Person: foaf_givenName: Holger foaf_name: Karl, Holger foaf_surname: Karl foaf_workInfoHomepage: http://www.librecat.org/personId=126 dct_date: 2021^xs_gYear dct_language: eng dct_title: Reinforcement Learning for Autonomous Vehicle Movements in Wireless Sensor Networks@ ...