Reinforcement Learning – alle Bücher

Aviv Tamar, Shie Mannor, Yishay Mansour
Reinforcement Learning Foundations

Bridging the gap between introductory texts and the specialized research literature, this is one of the first truly rigorous yet accessible treatments of modern reinforcement learning. Written by three le…

lieferbar ab 31.7.2026.

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Sean Meyn
Control Systems and Reinforcement Learning

"A high school student can create deep Q-learning code to control her robot, without any understanding of the meaning of "deep" or "Q", or why the code sometimes fails. This book …

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Zhiwei Qin (Tony), Xiaocheng Tang, Qingyang Li, Hongtu Zhu
Reinforcement Learning in the Ridesharing Marketplace

This book provides a comprehensive overview of reinforcement learning for ridesharing applications. The authors first lay out the fundamentals of the ridesharing system architectures and review the basics…

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Baihan Lin
Reinforcement Learning Methods in Speech and Language Technology

Signals and Communication Technology

This book offers a comprehensive guide to reinforcement learning (RL) and bandits methods, specifically tailored for advancements in speech and language technology. Starting with a foundational overview o…

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Aaron M. Roth, Dinesh Manocha, Ram D. Sriram, Elham Tabassi
Explainable and Interpretable Reinforcement Learning for Robotics

Synthesis Lectures on Artificial Intelligence and Machine Learning

This book surveys the state of the art in explainable and interpretable reinforcement learning (RL) as relevant for robotics. While RL in general has grown in popularity and been applied to increasingly c…

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Hang Wang, Sen Lin, Junshan Zhang
Continual and Reinforcement Learning for Edge AI

This book provides a comprehensive introduction to continual and reinforcement learning for edge AI, which investigates how to build an AI agent that can continuously solve new learning tasks and enhance …

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Rudy Milani
Advanced Automation for Comprehensible Causal Explanations of Reinforcement Learning Agents

This thesis introduces Auto-BENEDICT, a novel, fully automated methodology designed to generate human-comprehensible causal explanations for model-free Reinforcement Learning (RL) agents. The system addre…

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Bosen Lian, Wenqian Xue, Bahare Kiumarsi, Hamidreza Modares
Integral and Inverse Reinforcement Learning for Optimal Control Systems and Games

Integral and Inverse Reinforcement Learning for Optimal Control Systems and Games develops its specific learning techniques, motivated by application to autonomous driving and microgrid systems, with brea…

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Nathan Lambert
The Rlhf Book

Get a free eBook (PDF or ePub) from Manning as well as access to the online liveBook format (and its AI assistant that will answer your questions in any language) when you purchase the print book.This is …

lieferbar ab 28.7.2026.

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Jan Maetschke
Wirtschaftliche Leistungssteigerung von Produktionslinien

Die Dissertation entwickelt einen praxisgerechten Ansatz zur wirtschaftlichen Leistungssteigerung von Produktionslinien. Durch die Kombination simulationsbasierter Optimierung mit hierarchischem und heuri…

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Christiane Barz
Mathematik für Wirtschaftswissenschaftler

Nicht nur in den Wirtschaftswissenschaften wird die Bedeutung der Mathematik immer größer. In Zeiten von Big Data, Business Analytics und Reinforcement Learning können qualitativ gute, informierte Entsche…

lieferbar ab 7.8.2026.

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Christian Knaak
Echtzeitüberwachung und -optimierung der Nahtqualität beim Laserstrahlschweißen mittels bildgebender Sensorik und künstlicher Intelligenz

Herausforderungen wie steigende Qualitätsanforderungen und Kosteneffizienz erfordern innovative Lösungen für die effiziente Herstellung hochwertiger Produkte in der Automobilindustrie. Diese Arbeit stellt…

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Advances in Practical Applications of Agents, Multi-Agent Systems, and Computational Social Science: The PAAMS Collection

.- Main Track. .- Transformer Based Models for Offline Multi-Agent Reinforcement Learning. .- Theory and Practice of Natural Strategy Checking in Concurrent Games with Imperfect Information. .- Optimizing…

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Vikram Krishnamurthy
Partially Observed Markov Decision Processes

This survey of formulation, algorithms, and structural results in POMDPs focuses on underlying concepts and connections to real-world applications in controlled sensing, keeping technical machinery to a m…

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Proceedings of the 3rd International Conference on Computer Science's Complex Systems and Their Applications

Machine Learning-Based Intrusion Detection Systems for the Internet of Drones: A Systematic Mapping Study.- A comprehensive study on Artificial Intelligence of Things Optimization Approaches.- Fault Predi…

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Advances on Broad-Band and Wireless Computing, Communication and Applications

.- Game Theoretic Reinforcement Learning for Mobility-Aware Resource Allocation in 5G MIMO.- Cross-Domain Handover in 5G/6G Networks.- Mesh Router Optimization by WMN-PSOHCDGA Simulation System for a Smal…

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Advances on P2P, Parallel, Grid, Cloud and Internet Computing

.- Relation Extraction of Traditional Chinese Medicine Patents Based on Large Language Model and Diversified Semantic Interaction.- Semantic Multi-Agent Framework for Automated Cloud-Edge Pattern Discover…

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Artificial Intelligence XLII

.- Application Papers. .- Detect, Decide, Explain: An Intelligent Framework for Zero-Day Network Attack Detection (Best Application Paper). .- Evolutionary Algorithms. .- Evolutionary Optimization of Auto…

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Haesik Kim
Artificial Intelligence in the 6G Ecosystem

This textbook provides knowledge of artificial intelligence (AI), wireless communications, and cellular networks. It covers AI techniques such as unsupervised learning, supervised learning, reinforcement …

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Rajendra Akerkar
Artificial Intelligence

Part 1: Foundations of artificial intelligence.- The genesis of artificial intelligence: Origins and evaluation.- The dawn of AI: Early innovations and discoveries.- Part 2: The learning revolution: Data-…

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