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Reinforcement & Systemic Mchin - (IEEE Press Systems Science and Engineering) by  Parag Kulkarni (Hardcover) - 1 of 1

Reinforcement & Systemic Mchin - IEEE Press Systems Science and Engineering by Parag Kulkarni Hardcover

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Highlights

  • About the Author: Parag Kulkarni, PhD, DSc, is the founder and Chief Scientist of EKLat Research where he has empowered businesses through machine learning, knowledge management, and systemic management.
  • 320 Pages
  • Technology, Electronics
  • Series Name: IEEE Press Systems Science and Engineering

Description



About the Book



"Reinforcement and Systemic Machine Learning for Decision Making explores a newer and growing avenue of machine learning algorithm in the area of computational intelligence. This book focuses on reinforcement and systemic learning to build a new learning paradigm, which makes effective use of these learning methodologies to increase machine intelligence and help us in building the advance machine learning applications. Illuminating case studies reflecting the authors' industrial experiences and pragmatic downloadable tutorials are available for researchers and professionals"--



From the Back Cover



Reinforcement and Systemic Machine Learning for Decision Making

There are always difficulties in making machines that learn from experience. Complete information is not always available--or it becomes available in bits and pieces over a period of time. With respect to systemic learning, there is a need to understand the impact of decisions and actions on a system over that period of time. This book takes a holistic approach to addressing that need and presents a new paradigm--creating new learning applications and, ultimately, more intelligent machines.

The first book of its kind in this new and growing field, Reinforcement and Systemic Machine Learning for Decision Making focuses on the specialized research area of machine learning and systemic machine learning. It addresses reinforcement learning and its applications, incremental machine learning, repetitive failure-correction mechanisms, and multiperspective decision making.

Chapters include:

  • Introduction to Reinforcement and Systemic Machine Learning
  • Fundamentals of Whole-System, Systemic, and Multiperspective Machine Learning
  • Systemic Machine Learning and Model
  • Inference and Information Integration
  • Adaptive Learning
  • Incremental Learning and Knowledge Representation
  • Knowledge Augmentation: A Machine Learning Perspective
  • Building a Learning System With the potential of this paradigm to become one of the more utilized in its field, professionals in the area of machine and systemic learning will find this book to be a valuable resource.



About the Author



Parag Kulkarni, PhD, DSc, is the founder and Chief Scientist of EKLat Research where he has empowered businesses through machine learning, knowledge management, and systemic management. He has been working within the IT industry for over twenty years. The recipient of several awards, Dr. Kulkarni is a pioneer in the field. His areas of research and product development include M-maps, intelligent systems, text mining, image processing, decision systems, forecasting, IT strategy, artificial intelligence, and machine learning. Dr. Kulkarni has over 100 research publications including several books.
Dimensions (Overall): 9.2 Inches (H) x 6.2 Inches (W) x .9 Inches (D)
Weight: 1.3 Pounds
Suggested Age: 22 Years and Up
Number of Pages: 320
Genre: Technology
Sub-Genre: Electronics
Series Title: IEEE Press Systems Science and Engineering
Publisher: Wiley-IEEE Press
Theme: General
Format: Hardcover
Author: Parag Kulkarni
Language: English
Street Date: August 14, 2012
TCIN: 1008778864
UPC: 9780470919996
Item Number (DPCI): 247-17-0389
Origin: Made in the USA or Imported
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Shipping details

Estimated ship dimensions: 0.9 inches length x 6.2 inches width x 9.2 inches height
Estimated ship weight: 1.3 pounds
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