F. Richard Yu – författare

This book features the major research advances on integrated networking, caching, and computing. Information-centric networking-based caching is one of the promising techniques for future networks. The cloud computing paradigm has been widely adopted to enable convenient, on-demand network access to a shared pool of configurable computing resources. In addition, fog/edge computing is proposed to deploy computing resources closer to end devices. From the perspective of applications, network, cache and compute are underlying enabling resources. How to manage, control and optimize these resources can have significant impacts on application performance.

This book features the major research advances on integrated networking, caching, and computing. Information-centric networking-based caching is one of the promising techniques for future networks. The cloud computing paradigm has been widely adopted to enable convenient, on-demand network access to a shared pool of configurable computing resources. In addition, fog/edge computing is proposed to deploy computing resources closer to end devices. From the perspective of applications, network, cache and compute are underlying enabling resources. How to manage, control and optimize these resources can have significant impacts on application performance.

This Springerbrief presents a deep reinforcement learning approach to wireless systems to improve system performance. Particularly, deep reinforcement learning approach is used in cache-enabled opportunistic interference alignment wireless networks and mobile social networks. Simulation results with different network parameters are presented to show the effectiveness of the proposed scheme.

 There is a phenomenal burst of research activities in artificial intelligence, deep reinforcement learning and wireless systems. Deep reinforcement learning has been successfully used to solve many practical problems. For example, Google DeepMind adopts this method on several artificial intelligent projects with big data (e.g., AlphaGo), and gets quite good results..

 Graduate students in electrical and computer engineering, as well as computer science will find this brief useful as a study guide. Researchers, engineers, computer scientists, programmers, and policy makers will also find this brief to be a useful tool. 

This book introduces a variety of intelligence phenomena starting from the birth of the universe, including intelligence in physics, intelligence in chemistry, intelligence in biology, intelligence in humans and intelligence in machines. It uncovers the mystery of intelligence to the world and explores the natural phenomenon of intelligence. If understanding intelligence is regarded as a journey of a thousand miles, then this book is the first step to try. In the process of studying the phenomenon of intelligence and the nature of intelligence, our eyes cannot be limited to human intelligence. Instead, one should put our vision beyond human intelligence, consider different things in the universe, reach a new level, and study and explore the phenomenon of intelligence and the essence of intelligence on a new level.

This book can be used as a reference for students and researchers working in the artificial intelligence areas.  It is also positioned as a popular science book interested in intelligent phenomena.