Reinforcement Learning (Hardcover)
Idioma: inglés
Editorial: De Gruyter, Berlin, 2026
- Tapa dura
- Nuevo

Librería: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
Vendedor de IberLibro desde 22 de junio de 2007
Condición: Nuevo
EUR 113,97
Cantidad disponible: 1 disponible
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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.…
N° de ref. del artículo 9783111633596
- Título
- Reinforcement Learning (Hardcover)
- Autor
- Madan Mohan Tito Ayyalasomayajula
- Editorial
- De Gruyter, Berlin
- Año de publicación
- 2026
- Estado
- new
- Encuadernación
- Hardcover
- Idioma
- inglés
- ISBN 10
- 3111633594
- ISBN 13
- 9783111633596
“Sinopsis” puede pertenecer a otra edición de este título.
Acerca del autor
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, big data, distributed systems, and advanced data engineering. Throughout his career, he has held key leadership positions, including Enterprise Cloud Solutions Architect at Toyota Motor North America, Enterprise Architect at Walgreens, Principal Architect at Mahindra Comviva, and he currently serves as a Senior Enterprise Architecture Lead at Infosys. Dr. Ayyalasomayajula holds a Doctorate in Computer Science from Aspen University and dual master's degrees from Osmania University. His work has been instrumental in architecting scalable, enterprise-grade data and AI platforms that address complex real-world business challenges and accelerate digital transformation initiatives across industries. As a published researcher, he has contributed to the advancement of artificial intelligence, machine learning, big data, and intelligent enterprise systems through technical publications, peer-reviewed research, and industry knowledge-sharing initiatives. A recognized thought leader in data and AI, Dr. Ayyalasomayajula is a Senior Member of both IEEE and the Institution of Engineering and Technology. He actively contributes to the global research community as a reviewer for leading journals and international conferences in artificial intelligence, reinforcement learning, machine learning, and big data technologies. His unique ability to bridge academic research with practical enterprise implementation enables him to deliver innovative, ethical, and future-ready technology solutions. Beyond his professional achievements, Dr. Ayyalasomayajula is a passionate mentor and innovation advocate who actively supports emerging technology professionals through research publications, industry forums, and knowledge-sharing initiatives. His work continues to influence the evolving landscape of AI, reinforcement learning, data architecture, and intelligent enterprise systems, with a strong commitment to responsible innovation and the societal advancement of technology.
Dr. Sivarethinamohan R is a Professor in Symbiosis Centre for Management Studies, Bengaluru campus, Symbiosis International Deemed University, Pune, India. He holds a doctoral degree from Bharathiar University, Coimbatore (Tamil Nadu). Dr. R. Sivarethinamohan teaches courses at Symbiosis that build on his research interests and is actively involved in consultancy work with companies in Bangalore, India. In his academic career spanning more than 30 years, Dr. R. Sivarethinamohan has participated in and presented research papers at national and international conferences and also holds nearly 62 publications in leading journals indexed in Scopus, 20 in the Web of Science, and 5 in the UCG CARE list to his credit. In addition to the 20 book chapters, Dr. Sivarethinamohan has published textbooks with (i) Tata McGraw Hill, New Delhi, titled "Operations Research", (ii) Prentice Hall of India, New Delhi, titled "Industrial Relations and Labour Welfare", and (iii). Sultan Chand & Son, titled "Engineering Economics and Financial Accounting" and (iv) CBA Publishers, titled "Principles of Management" and a few edited books. This research and academic experience have helped him to introduce innovations in the teaching methodology and to convey the practical application of the course effectively. He published two patents titled "Development of Smart System to Avoid Triples and Over Speed Control in Two Wheelers" (202041033794) on 21.08.2020 and "Development of Real-Time Traffic Control System Using Digital Image Processing" (202041038823) on 25.09.2020. In the year 2024, he got two design patents (Grant) as a single inventor, titled 1. Office Table Device for Task Management and 2. Waste Management Alerting Device. He got the best paper award for the paper titled "Production and modifications of biochar to engineered materials and its application for environmental sustainability: A review," published in 2023-2024 in BIOCHAR (Q1 Journal).
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