Learning for Decision and Control in Stochastic Networks Longbo Huang Springer International Publishing AG

Κωδικός: 2553833

Περιγραφή για Learning for Decision and Control in Stochastic Networks Longbo Huang Springer International Publishing AG

This book introduces the Learning-Augmented Network Optimization (LANO) paradigm, which interconnects network optimization with the emerging AI theory and algorithms and has been receiving a growing attention in network research. The authors present the topic based on a general stochastic network optimization model, and review several important theoretical tools that are widely adopted in network research, including convex optimization, the drift method, and mean-field analysis. The book then covers several popular learning-based methods, i.e., learning-augmented drift, multi-armed bandit and reinforcement learning, along with applications in networks where the techniques have been successfully applied. The authors also provide a discussion on potential future directions and challenges. Σελίδες: 71, Διαστάσεις: 16.8x16.8cm

Αγορά Learning for Decision and Control in Stochastic Networks Longbo Huang Springer International Publishing AG

Επισκέψου το κατάστημα Book Odyssey για να δεις περισσότερες λεπτομέρειες και φωτογραφίες για το Learning for Decision and Control in Stochastic Networks Longbo Huang Springer International Publishing AG. Για αγορά του Learning for Decision and Control in Stochastic Networks Longbo Huang Springer International Publishing AG πρέπει να επισκεφτείς το κατάστημα Book Odyssey.