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市場調查報告書

強化學習 (Reinforcement Learning):技術的介紹

Reinforcement Learning: An Introduction to the Technology

出版商 BCC Research 商品編碼 923548
出版日期 內容資訊 英文 17 Pages
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強化學習 (Reinforcement Learning):技術的介紹 Reinforcement Learning: An Introduction to the Technology
出版日期: 2020年01月24日內容資訊: 英文 17 Pages
簡介

本報告提供強化學習 (Reinforcement Learning)的技術調查,技術定義和概要,對市場成長的各種影響因素及市場機會分析,各種產業上未來的用途,主要企業的簡介,市場潛在性分析等彙整資料。

第1章 強化學習

  • 強化學習概要
  • AI與機器學習
  • 強化學習 vs 有教師學習 vs 無教師學習
  • 強化學習演算法的方法
  • 強化學習的特徵
  • 市場動態
    • 促進因素
    • 阻礙因素
    • 機會
  • 強化學習的課題
  • 強化學習的未來的方面
  • 各種產業上強化學習的未來用途
    • 電腦叢集的資源管理
    • 訊號控制
    • 機器人工學
    • 網站系統配置
    • 化學
    • 個性化的提案
    • 競標、廣告
    • 遊戲
  • 市場潛在性
  • 致力於強化學習的企業
    • BONSAI
    • DEEPMIND TECHNOLOGIES
    • MALUUBA INC.
    • MATHWORKS

第2章 參考文獻

目錄
Product Code: IFT193A

Report Highlights:

This study will serve as a guide and benchmark for technology vendors, manufacturers of the hardware that supports AI, as well as the end users who will finally use this technology. Decision-makers will find the information useful in developing business strategies and in identifying areas for research and development.

Report Includes:

  • A general framework for deep Reinforcement Learning (RL) - also known as a semi-supervised learning model in machine learning paradigm
  • Assessing the breadth and depth of RL applications in real-world domains, including increased data efficiency and stability as well as multi-tasking
  • Understanding of the RL algorithm from different aspects; and persuade the decision makers and researchers to put more efforts on RL research

Table of Contents

Chapter 1: Reinforcement Learning

  • Reasons for Doing This Report
  • Intended Audience
  • Introduction to Reinforcement Learning
  • Artificial Intelligence and Machine Learning
    • Four Main Types of Machine Learning
  • Reinforcement Learning vs. Supervised Learning vs. Unsupervised Learning
  • Approaches to Reinforcement Learning Algorithms
  • Characteristics of Reinforcement Learning
  • Market Dynamics
    • Drivers
    • Restraints
    • Opportunities
  • Challenges of Reinforcement Learning
    • Slower Interaction with Real Systems as Compared to Faster Simulated Environments
    • Higher Variance and Instability
    • Absence of Reproducibility Due to Lack of Standardized Benchmarks, Frameworks and Evaluation Metrics
    • Inappropriate Definition of Rewards, Actions and States
    • Lack of Generalization
  • Future Aspects of Reinforcement Learning
  • Future Applications of Reinforcement Learning Across Verticals
    • Resources Management in Computer Clusters
    • Traffic Light Control
    • Robotics
    • Web System Configuration
    • Chemistry
    • Personalized Recommendations
    • Bidding and Advertising
    • Games
  • Market Potential
  • Companies Working on Reinforcement Learning
    • BONSAI
    • DEEPMIND TECHNOLOGIES
    • MALUUBA INC.
    • MATHWORKS
    • Analyst Credentials
  • Related BCC Research Reports

Chapter 2: Bibliography

List of Tables

  • Table 1: Reinforcement Learning vs. Supervised Learning vs. Unsupervised Learning
  • Table 2: Global Machine Learning Market, by Region, Through 2024

List of Figures

  • Figure 1: Reinforcement Learning Process
  • Figure 2: Reinforcement Learning Workflow
  • Figure 3: Artificial Intelligence vs. Machine Learning vs. Reinforcement Learning
  • Figure 4: Machine Learning Applications
  • Figure 5: Types of Machine Learning
  • Figure 6: Reinforcement Learning Market Dynamics
  • Figure 7: Global Machine Learning Market, by Region, 2018-2024