Robot Learning from Human Teachers (Synthesis Lectures on Artificial Intelligence and Machine Le)
暫譯: 從人類教師學習的機器人(人工智慧與機器學習綜合講座)

Sonia Chernova, Andrea L. Thomaz

  • 出版商: Morgan & Claypool
  • 出版日期: 2014-04-01
  • 售價: $1,600
  • 貴賓價: 9.5$1,520
  • 語言: 英文
  • 頁數: 122
  • 裝訂: Paperback
  • ISBN: 1627051996
  • ISBN-13: 9781627051996
  • 相關分類: 人工智慧機器人製作 Robots
  • 海外代購書籍(需單獨結帳)

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商品描述

Learning from Demonstration (LfD) explores techniques for learning a task policy from examples provided by a human teacher. The field of LfD has grown into an extensive body of literature over the past 30 years, with a wide variety of approaches for encoding human demonstrations and modeling skills and tasks. Additionally, we have recently seen a focus on gathering data from non-expert human teachers (i.e., domain experts but not robotics experts). In this book, we provide an introduction to the field with a focus on the unique technical challenges associated with designing robots that learn from naive human teachers. We begin, in the introduction, with a unification of the various terminology seen in the literature as well as an outline of the design choices one has in designing an LfD system. Chapter 2 gives a brief survey of the psychology literature that provides insights from human social learning that are relevant to designing robotic social learners. Chapter 3 walks through an LfD interaction, surveying the design choices one makes and state of the art approaches in prior work. First, is the choice of input, how the human teacher interacts with the robot to provide demonstrations. Next, is the choice of modeling technique. Currently, there is a dichotomy in the field between approaches that model low-level motor skills and those that model high-level tasks composed of primitive actions. We devote a chapter to each of these. Chapter 7 is devoted to interactive and active learning approaches that allow the robot to refine an existing task model. And finally, Chapter 8 provides best practices for evaluation of LfD systems, with a focus on how to approach experiments with human subjects in this domain.

Table of Contents: Introduction / Human Social Learning / Modes of Interaction with a Teacher / Learning Low-Level Motion Trajectories / Learning High-Level Tasks / Refining a Learned Task / Designing and Evaluating an LfD Study / Future Challenges and Opportunities / Bibliography / Authors' Biographies

商品描述(中文翻譯)

學習示範 (Learning from Demonstration, LfD) 探索從人類教師提供的範例中學習任務策略的技術。在過去的 30 年中,LfD 領域已發展成為一個龐大的文獻體系,擁有多種編碼人類示範和建模技能及任務的方法。此外,我們最近看到對於從非專家人類教師(即領域專家但不是機器人專家)收集數據的關注。在本書中,我們提供了該領域的介紹,重點關注設計從天真的人類教師學習的機器人所面臨的獨特技術挑戰。我們在引言中開始統一文獻中出現的各種術語,並概述設計 LfD 系統時的設計選擇。第二章簡要調查了心理學文獻,提供了與設計機器人社會學習者相關的人類社會學習的見解。第三章介紹了一個 LfD 互動,調查了設計選擇和先前工作的最新方法。首先是輸入的選擇,即人類教師如何與機器人互動以提供示範。接下來是建模技術的選擇。目前,該領域在建模低階運動技能和建模由基本動作組成的高階任務之間存在二分法。我們為每個主題分配了一章。第七章專注於互動和主動學習方法,允許機器人完善現有的任務模型。最後,第八章提供了 LfD 系統評估的最佳實踐,重點在於如何在該領域中進行人類受試者實驗。

目錄:引言 / 人類社會學習 / 與教師的互動模式 / 學習低階運動軌跡 / 學習高階任務 / 完善學習的任務 / 設計和評估 LfD 研究 / 未來挑戰與機會 / 參考文獻 / 作者簡介