{
"item_title" : "Adaptive Representations for Reinforcement Learning",
"item_author" : [" Shimon Whiteson "],
"item_description" : "Presenting the main results of new algorithms for reinforcement learning, this book also introduces a novel method for devising input representations as well as presenting a way to find a minimal set of features sufficient to describe the agent's current state.",
"item_img_path" : "https://covers2.booksamillion.com/covers/bam/3/64/242/231/3642422314_b.jpg",
"price_data" : {
"retail_price" : "109.99", "online_price" : "109.99", "our_price" : "109.99", "club_price" : "109.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : ""
}
}
Adaptive Representations for Reinforcement Learning
Overview
Presenting the main results of new algorithms for reinforcement learning, this book also introduces a novel method for devising input representations as well as presenting a way to find a minimal set of features sufficient to describe the agent's current state.
This item is Non-Returnable
Customers Also Bought
Details
- ISBN-13: 9783642422317
- ISBN-10: 3642422314
- Publisher: Springer
- Publish Date: November 2014
- Dimensions: 9.21 x 6.14 x 0.28 inches
- Shipping Weight: 0.43 pounds
- Page Count: 116
Related Categories
