Inicio > > Ciencias de la computación > Inteligencia artificial > Decision Making Under Uncertainty and Reinforcement Learning
Decision Making Under Uncertainty and Reinforcement Learning

Decision Making Under Uncertainty and Reinforcement Learning

Christos Dimitrakakis / Ronald Ortner

196,29 €
IVA incluido
Consulta disponibilidad
Editorial:
Springer Nature B.V.
Año de edición:
2022
Materia
Inteligencia artificial
ISBN:
9783031076121

Selecciona una librería:

  • Librería Samer Atenea
  • Librería Aciertas (Toledo)
  • Kálamo Books
  • Librería Perelló (Valencia)
  • Librería Elías (Asturias)
  • Donde los libros
  • Librería Kolima (Madrid)
  • Librería Proteo (Málaga)

This book presents recent research in decision making under uncertainty, in particular reinforcement learning and learning with expert advice. The core elements of decision theory, Markov decision processes and reinforcement learning have not been previously collected in a concise volume. Our aim with this book was to provide a solid theoretical foundation with elementary proofs of the most important theorems in the field, all collected in one place, and not typically found in introductory textbooks.  This book is addressed to graduate students that are interested in statistical decision making under uncertainty and the foundations of reinforcement learning.  

Artículos relacionados

  • Artificial Cognition Systems
    ...
  • Cross-Disciplinary Applications of Artificial Intelligence and Pattern Recognition
    Vijay Kumar Mago
    The need for intelligent machines in areas such as medical diagnostics, biometric security systems, and image processing motivates researchers to develop and explore new techniques, algorithms, and applications in this evolving field. Cross-Disciplinary Applications of Artificial Intelligence and Pattern Recognition: Advancing Technologies provides a common platform for researc...
  • Emerging Applications of Natural Language Processing
    Over the last few years, the area of Natural Language Processing has drastically grown in recognition, not only within the research and development community, but also with industry professionals. As NLP continues to be discussed and researched, certain areas continue to grow and mature. As a result, the need for advanced research and information is in high demand. Emerging App...
  • Androids, Cyborgs, and Robots in Contemporary Culture and Society
    Steven John Thompson
    Mankind’s dependence on artificial intelligence and robotics is increasing rapidly as technology becomes more advanced. Finding a way to seamlessly intertwine these two worlds will help boost productivity in society and aid in a variety of ways in modern civilization. Androids, Cyborgs, and Robots in Contemporary Culture and Society is an essential scholarly resource that delve...
  • Deep Learning Innovations and Their Convergence With Big Data
    The expansion of digital data has transformed various sectors of business such as healthcare, industrial manufacturing, and transportation. A new way of solving business problems has emerged through the use of machine learning techniques in conjunction with big data analytics. Deep Learning Innovations and Their Convergence With Big Data is a pivotal reference for the latest sc...
  • Computational Psychoanalysis and Formal Bi-Logic Frameworks
    Giuseppe Iurato
    Computational psychoanalysis is a new field stemming from Freudian psychoanalysis. The new area aims to understand the primary formal structures and running mechanisms of the unconscious while implementing them into computer sciences. Computational Psychoanalysis and Formal Bi-Logic Frameworks provides emerging information on this new field which uses psychoanalysis and the unc...

Otros libros del autor

  • Decision Making Under Uncertainty and Reinforcement Learning
    Christos Dimitrakakis / Ronald Ortner
    This book presents recent research in decision making under uncertainty, in particular reinforcement learning and learning with expert advice. The core elements of decision theory, Markov decision processes and reinforcement learning have not been previously collected in a concise volume. Our aim with this book was to provide a solid theoretical foundation with elementary proof...
    Disponible

    197,64 €

  • Decision Making Under Uncertainty and Reinforcement Learning
    Christos Dimitrakakis / Ronald Ortner
    This book presents recent research in decision making under uncertainty, in particular reinforcement learning and learning with expert advice. The core elements of decision theory, Markov decision processes and reinforcement learning have not been previously collected in a concise volume. Our aim with this book was to provide a solid theoretical foundation with elementary proof...
    Disponible

    48,00 €