ISBN: 9783111633596 - reinforcement learning: autonomous systems, ethical ai, robotics (10 Ergebnisse)

Zustand: New. Dr. Madan Mohan Tito Ayyalasomayajula is a distinguished researcher, published author, and technology leader with over two decades of experience in enterprise architecture, artificial intelligence, reinforcement learning, cloud computing.

Hardcover. Zustand: Brand New. 859 pages. 6.69x2.00x9.45 inches. In Stock.

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.…

Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 843 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

Zustand: New. 2026. 1st Edition. hardcover. . . . . .

Zustand: New. 2026. 1st Edition. hardcover. . . . . . Books ship from the US and Ireland.

Hardcover. Zustand: new. Hardcover. 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 RLs 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 todays 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. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Hardcover. Zustand: new. Hardcover. 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 RLs 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 todays 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. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Hardcover. Zustand: new. Hardcover. 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 RLs 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 todays 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…