reinforcement learning autonomous systems (7 Ergebnisse)

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Zustand: New. In.

Paperback. Zustand: Brand New. 109 pages. 6.14x0.23x9.21 inches. In Stock.

Taschenbuch. Zustand: Neu. Reinforcement Learning in Robotics and Autonomous Systems | The State of the Art | N. S. Usha (u. a.) | Taschenbuch | Englisch | 2025 | LAP LAMBERT Academic Publishing | EAN 9786208434175 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Taschenbuch. Zustand: Neu. Neuware - Cognitive Electronic Warfare and Autonomous Spectrum Management - Volume IIIEdge AI, Distributed Electromagnetic Intelligence, and Autonomous Spectrum WarfareThe electromagnetic battlespace is becoming autonomous.As edge AI, distributed cognition, RFSoCs, and intelligent wireless systems converge, the next generation of spectrum warfare is shifting from centralized control toward machine-speed autonomous coordination across contested electromagnetic environments.Volume III of The Cognitive Spectrum Series explores the execution layer of intelligent spectrum systems-where AI inference, SDR architectures, distributed decision systems, and real-time RF orchestration merge into adaptive electromagnetic ecosystems.Blending: - Edge AI inferencing, - RFSoC acceleration, - FPGA execution pipelines, - distributed cognitive networking, - adversarial machine learning, - autonomous EW architectures, - and real-time SDR orchestration, this volume presents a systems-engineering framework for understanding how future wireless systems will operate under extreme latency, bandwidth, synchronization, and adversarial constraints.Topics include: - TensorRT and ONNX Runtime- RFSoC and FPGA acceleration- Zero-copy SDR architectures- Shared-memory inference pipelines- Distributed spectrum intelligence- AI-native wireless orchestration- GNSS spoofing and navigation warfare- Cognitive mesh networking- Adversarial machine learning in RF- Autonomous EW coordination- Real-time scheduling systems- Edge AI for SDR platforms- Future 6G and THz systemsDesigned for: - RF engineers, - SDR developers, - FPGA architects, - AI researchers, - defense technologists, - edge-computing engineers, - and advanced wireless systems designers, this volume bridges the gap between theoretical AI systems and operational autonomous electromagnetic architectures.The future of spectrum warfare will not be manually controlled.It will be coordinated by intelligent machines operating at machine speed.

Buch. Zustand: Neu. Reinforcement Learning | Autonomous Systems, Ethical AI, Robotics | Madan Mohan Tito Ayyalasomayajula (u. a.) | Buch | XVIII | Englisch | 2026 | De Gruyter | EAN 9783111633596 | Verantwortliche Person für die EU: Walter de Gruyter GmbH, De Gruyter GmbH, Genthiner Str. 13, 10785 Berlin, productsafety[at]degruyterbrill[dot]com | Anbieter: preigu.

Buch. Zustand: Neu. Neuware - This book critically examines the ongoing transformation within Reinforcement Learning (RL), driven by significant advancements in computational power, algorithmic innovation, and interdisciplinary applications. As a vital branch of artificial intelligence, RL facilitates agents' learning through interactions with their environment, increasingly underpinning the optimization of complex systems and enhancing decision-making capabilities. Its diverse applications, spanning autonomous vehicles, robotics, personalized recommendations, and financial trading, underscore RL's role as a foundational technology for future innovations. Given the pervasive integration of artificial intelligence across industries, a reimagining of RL is essential to address the multifaceted challenges posed by today's complex and dynamic environments. This work rigorously bridges theoretical developments with practical implementations, elucidating how RL can be harnessed to design adaptive systems capable of continuous improvement. By engaging with these emerging paradigms, this publication provides scholars and practitioners with the critical insights necessary to advance RL and AI, positioning them at the forefront of the next wave of technological progress.