Learning By Playing Solving Sparse Reward Tasks From Scratch
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Computer Vision – ECCV 2024
The multi-volume set of LNCS books with volume numbers 15059 upto 15147 constitutes the refereed proceedings of the 18th European Conference on Computer Vision, ECCV 2024, held in Milan, Italy, during September 29–October 4, 2024. The 2387 papers presented in these proceedings were carefully reviewed and selected from a total of 8585 submissions. They deal with topics such as Computer vision, Machine learning, Deep neural networks, Reinforcement learning, Object recognition, Image classification, Image processing, Object detection, Semantic segmentation, Human pose estimation, 3D reconstruction, Stereo vision, Computational photography, Neural networks, Image coding, Image reconstruction and Motion estimation.
Mathematical Foundations of Reinforcement Learning
This book provides a mathematical yet accessible introduction to the fundamental concepts, core challenges, and classic reinforcement learning algorithms. It aims to help readers understand the theoretical foundations of algorithms, providing insights into their design and functionality. Numerous illustrative examples are included throughout. The mathematical content is carefully structured to ensure readability and approachability. The book is divided into two parts. The first part is on the mathematical foundations of reinforcement learning, covering topics such as the Bellman equation, Bellman optimality equation, and stochastic approximation. The second part explicates reinforcement learning algorithms, including value iteration and policy iteration, Monte Carlo methods, temporal-difference methods, value function methods, policy gradient methods, and actor-critic methods. With its comprehensive scope, the book will appeal to undergraduate and graduate students, post-doctoral researchers, lecturers, industrial researchers, and anyone interested in reinforcement learning.
The Proceedings of 2024 International Conference on Artificial Intelligence and Autonomous Transportation
This book reflects the latest research trends, methods and experimental results in the field of Artificial Intelligence and Autonomous Transportation, which covers abundant state-of-the-art research theories and ideas. As a vital research area that is highly relevant to current developments in a number of technological domains, the topics covered include Autonomous Transportation Systems, Autonomous Transportation Management and Control Technology, Autonomous Transportation Equipment Technology, Vehicular Networking and Information Security, Emerging Technologies and Future Mobility, Intelligent water transportation technology, Cross-Domain Transportation Technology, and so on. The goal of the proceedings is to provide a major interdisciplinary forum for researchers, engineers, academics, and industry professionals to present the most innovative research and development in the field of Artificial Intelligence and Autonomous Transportation. Engineers and researchers from academia, industry, and government will also explore an insight view of the solutions that combine ideas from multiple disciplines in this area. The volumes serve as an excellent reference work for researchers and graduate students working in the areas of rail transportation, electrical engineering, and information technology.