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Reinforcement Learning (RL) is a very dynamic area in terms of theory and application. This book brings together many different aspects of the current research on several fields associated to RL which has been growing rapidly, producing a wide variety of learning algorithms for different applications. Based on 24 Chapters, it covers a very broad variety of topics in RL and their application in autonomous systems. A set of chapters in this book provide a general overview of RL while other chapters focus mostly on the applications of RL paradigms: Game Theory, Multi-Agent Theory, Robotic, Networking Technologies, Vehicular Navigation, Medicine and Industrial Logistic.
Artificial intelligence. --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Machine learning
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Machine Learning can be defined in various ways related to a scientific domain concerned with the design and development of theoretical and implementation tools that allow building systems with some Human Like intelligent behavior. Machine learning addresses more specifically the ability to improve automatically through experience.
Graphical modeling (Statistics) --- Multivariate analysis --- Graphic methods --- Machine learning
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The analysis of QoE is not an easy task, especially for multimedia services, because all the factors (technical and non-technical) that directly or indirectly influence the user-perceived quality have to be considered. This book describes different methods to investigate users' QoE from the viewpoint of technical and non-technical parameters using multimedia services. It discusses the subjective methods for both controlled and uncontrolled environments. Collected datasets are used to analyze users' profiles, which sheds light on key factors to help network service providers understand end-users' behavior and expectations. Important adaptive video streaming technologies are discussed that run on unmanaged networks to achieve certain QoS features. The authors present a scheduling method to allocate resources to the end-user based on users' QoE and optimizes the power efficiency of users' device for LTE-A. Lastly, two key aspects of 5G networks are presented: QoE using multimedia services (VoIP and video), and power-saving model for mobile device and virtual base station.
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