menu
{ "item_title" : "Continual and Reinforcement Learning for Edge AI", "item_author" : [" Hang Wang", "Sen Lin", "Junshan Zhang "], "item_description" : "This book provides a comprehensive introduction to continual and reinforcement learning for edge AI, which investigates how to build an AI agent that can continuously solve new learning tasks and enhance the AI at resource-limited edge devices. The authors introduce readers to practical frameworks and in-depth algorithmic foundations. The book surveys the recent advances in the area, coming from both academic researchers and industry professionals. The authors also present their own research findings on continual and reinforcement learning for edge AI. The book also covers the practical applications of the topic and identifies exciting future research opportunities.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/3/03/184/362/3031843622_b.jpg", "price_data" : { "retail_price" : "49.99", "online_price" : "49.99", "our_price" : "49.99", "club_price" : "49.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Continual and Reinforcement Learning for Edge AI|Hang Wang

Continual and Reinforcement Learning for Edge AI : Framework, Foundation, and Algorithm Design

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

Overview

This book provides a comprehensive introduction to continual and reinforcement learning for edge AI, which investigates how to build an AI agent that can continuously solve new learning tasks and enhance the AI at resource-limited edge devices. The authors introduce readers to practical frameworks and in-depth algorithmic foundations. The book surveys the recent advances in the area, coming from both academic researchers and industry professionals. The authors also present their own research findings on continual and reinforcement learning for edge AI. The book also covers the practical applications of the topic and identifies exciting future research opportunities.

This item is Non-Returnable

Details

  • ISBN-13: 9783031843624
  • ISBN-10: 3031843622
  • Publisher: Springer
  • Publish Date: May 2025
  • Dimensions: 9.61 x 6.69 x 0.69 inches
  • Shipping Weight: 1.42 pounds
  • Page Count: 265

Related Categories

You May Also Like...

    1

BAM Customer Reviews