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Reinforcement Learning for Sports Analytics

Reinforcement Learning for Sports Analytics
体育分析的强化学习
批准号:
521357-2018
负责人:
Poupart, Pascal
金额:
$14.53万
依托单位:
依托单位国家:
加拿大
项目类别:
Strategic Projects - Group
财政年份:
2019
资助国家:
加拿大
项目状态:
已结题
起止时间:
2019-01-01 至 2020-12-31

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中文摘要
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英文摘要
Our project develops novel machine learning algorithms for interpreting complex, multi-agent scenarios. We will advance the state of the art in deep reinforcement learning methods to enable analysis of continuous-flow input data. The collaboration with our industrial partner will tackle open problems in deep reinforcement learning that can result in richer capabilities in sports analytics for ice hockey and other continuous-flow sports such as basketball and soccer. Deep reinforcement learning, is a breakthrough technology with prominent successes in games such as Go (AlphaGo) and Chess (AlphaZero). This project will push deep reinforcement learning further into the physical world, with multi-person, complex scenarios arising from real-world noisy data sources. We will develop fundamental algorithmic advances and apply them to tasks including: - player evaluation - event predictions (match outcomes, next action, expected scores) - recognizing types of players, teams, play sequences, and tactics - identifying characteristic strengths and weaknesses of players and teams. Our partner is the Montreal-based company SPORTLOGiQ, which uses advanced computer vision to extract information about events from video of sports matches. Their information is more detailed than that provided by any other company or organization. The market for sports analytics is growing rapidly, with major international companies receiving millions of investment dollars. This project will build significant Canadian capacity in sports analytics, support academic research, advance commercialization in the sports industry, and train highly qualified personnel. Canada has achieved a position of leadership in reinforcement learning, through excellent researchers who have attracted companies such as Google's DeepMind to set up Canadian labs. The proposed research will contribute to Canada's reinforcement learning ecosystem by establishing novel algorithmic contributions for a major application area with great commercial potential.
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Robust and Sample Efficient Reinforcement Learning
  • 批准号:
    RGPIN-2019-05014
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $4.01万
  • 财政年份:
    2022
  • 负责人:
    Poupart, Pascal
  • 依托单位:
Robust and Sample Efficient Reinforcement Learning
  • 批准号:
    RGPIN-2019-05014
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $4.01万
  • 财政年份:
    2021
  • 负责人:
    Poupart, Pascal
  • 依托单位:
Robust and Sample Efficient Reinforcement Learning
  • 批准号:
    RGPIN-2019-05014
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $4.01万
  • 财政年份:
    2020
  • 负责人:
    Poupart, Pascal
  • 依托单位:
Reinforcement Learning for Sports Analytics
  • 批准号:
    521357-2018
  • 项目类别:
    Strategic Projects - Group
  • 资助金额:
    $14.59万
  • 财政年份:
    2020
  • 负责人:
    Poupart, Pascal
  • 依托单位:
国内基金
海外基金
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