{"product_id":"2724654","title":"Partially Observed Markov Decision Processes : Filtering, Learning and Controlled Sensing","description":"This comprehensive textbook delves into the world of partially observed Markov decision processes, a complex field at the intersection of artificial intelligence, control theory, and signal processing. It explores the challenges of decision-making in environments where the full state of the system is not observable, and the impact of limited information on optimal control and learning. The book covers filtering techniques for estimating the underlying state, learning methods for adapting to changing environments, and controlled sensing strategies for minimizing the need for direct observation. Through its in-depth analysis and examples, this resource provides a thorough understanding of the theoretical foundations and practical applications of partially observed Markov decision processes. It is an essential reference for researchers, engineers, and students working in control systems, artificial intelligence, and related fields. By mastering the concepts presented, readers will be well-equipped to tackle the complexities of real-world decision-making under uncertainty.","brand":"Chalkys.com","offers":[{"title":"Default Title","offer_id":54700980535681,"sku":"2724654","price":122.48,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0056\/8043\/1219\/files\/41I1w8kjOdL.jpg?v=1757130187","url":"https:\/\/chalkys.com\/products\/2724654","provider":"Chalkys.com","version":"1.0","type":"link"}