menu
{ "item_title" : "Stochastic Learning and Optimization", "item_author" : [" Xi-Ren Cao "], "item_description" : "Performance optimization is vital in the design and operation of modern engineering systems, including communications, manufacturing, robotics, and logistics. Most engineering systems are too complicated to model, or the system parameters cannot be easily identified, so learning techniques have to be applied. This book provides a unified framework based on a sensitivity point of view. It combines currently prominent research on reinforcement learning / neuro-dynamic programming with a unique research approach based on sensitivity analysis and discrete-event systems concepts. This new perspective on a popular topic is presented by a well respected expert in the field.", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/1/44/194/222/144194222X_b.jpg", "price_data" : { "retail_price" : "219.99", "online_price" : "219.99", "our_price" : "219.99", "club_price" : "219.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Stochastic Learning and Optimization|Xi-Ren Cao

Stochastic Learning and Optimization : A Sensitivity-Based Approach

local_shippingShip to Me
In Stock.
FREE Shipping for Club Members help

Overview

Performance optimization is vital in the design and operation of modern engineering systems, including communications, manufacturing, robotics, and logistics. Most engineering systems are too complicated to model, or the system parameters cannot be easily identified, so learning techniques have to be applied. This book provides a unified framework based on a sensitivity point of view. It combines currently prominent research on reinforcement learning / neuro-dynamic programming with a unique research approach based on sensitivity analysis and discrete-event systems concepts. This new perspective on a popular topic is presented by a well respected expert in the field.

This item is Non-Returnable

Details

  • ISBN-13: 9781441942227
  • ISBN-10: 144194222X
  • Publisher: Springer
  • Publish Date: October 2010
  • Dimensions: 9.21 x 6.14 x 1.19 inches
  • Shipping Weight: 1.79 pounds
  • Page Count: 566

Related Categories

You May Also Like...

    1

BAM Customer Reviews