Learning and Search in Decision Domains Featuring Large Action Sets and Uncertainty

具有大型动作集和不确定性的决策域中的学习和搜索

基本信息

  • 批准号:
    RGPIN-2017-05271
  • 负责人:
  • 金额:
    $ 1.46万
  • 依托单位:
  • 依托单位国家:
    加拿大
  • 项目类别:
    Discovery Grants Program - Individual
  • 财政年份:
    2017
  • 资助国家:
    加拿大
  • 起止时间:
    2017-01-01 至 2018-12-31
  • 项目状态:
    已结题

项目摘要

Artificial Intelligence (AI) research has come a long way creating systems that challenge human supremacy in complex decision domains such as Chess, Poker, Jeopardy, stock trading, and recently image recognition, autonomous driving, and the Asian boardgame Go. By contrast, AI progress in popular video games (such as StarCraft) and complex imperfect information domains, in which information is hidden from agents, has been slow, and in many cases human experts can still easily outperform the best programs.
人工智能(AI)研究已经走过了漫长的道路,创造了挑战人类在国际象棋、扑克、危险、股票交易等复杂决策领域的霸权的系统,最近还有图像识别、自动驾驶和亚洲棋盘游戏围棋。相比之下,人工智能在流行的视频游戏(如《星际争霸》)和复杂的不完美信息领域(其中信息对智能体隐藏)的进展缓慢,在许多情况下,人类专家仍然可以轻松超越最好的程序。

项目成果

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Buro, Michael其他文献

Real-Time Strategy Game Competitions
  • DOI:
    10.1609/aimag.v33i3.2419
  • 发表时间:
    2012-09-01
  • 期刊:
  • 影响因子:
    0.9
  • 作者:
    Buro, Michael;Churchill, David
  • 通讯作者:
    Churchill, David

Buro, Michael的其他文献

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{{ truncateString('Buro, Michael', 18)}}的其他基金

Learning and Search in Decision Domains Featuring Large Action Sets and Uncertainty
具有大型动作集和不确定性的决策域中的学习和搜索
  • 批准号:
    RGPIN-2018-06677
  • 财政年份:
    2022
  • 资助金额:
    $ 1.46万
  • 项目类别:
    Discovery Grants Program - Individual
Learning and Search in Decision Domains Featuring Large Action Sets and Uncertainty
具有大型动作集和不确定性的决策域中的学习和搜索
  • 批准号:
    RGPIN-2018-06677
  • 财政年份:
    2021
  • 资助金额:
    $ 1.46万
  • 项目类别:
    Discovery Grants Program - Individual
Learning and Search in Decision Domains Featuring Large Action Sets and Uncertainty
具有大型动作集和不确定性的决策域中的学习和搜索
  • 批准号:
    RGPIN-2018-06677
  • 财政年份:
    2020
  • 资助金额:
    $ 1.46万
  • 项目类别:
    Discovery Grants Program - Individual
Learning and Search in Decision Domains Featuring Large Action Sets and Uncertainty
具有大型动作集和不确定性的决策域中的学习和搜索
  • 批准号:
    RGPIN-2018-06677
  • 财政年份:
    2019
  • 资助金额:
    $ 1.46万
  • 项目类别:
    Discovery Grants Program - Individual
Learning and Search in Decision Domains Featuring Large Action Sets and Uncertainty
具有大型动作集和不确定性的决策域中的学习和搜索
  • 批准号:
    RGPIN-2018-06677
  • 财政年份:
    2018
  • 资助金额:
    $ 1.46万
  • 项目类别:
    Discovery Grants Program - Individual
"Search, Opponent Modelling, Cooperation, and State Inference in Complex Imperfect Information Domains."
“复杂不完美信息域中的搜索、对手建模、合作和状态推理。”
  • 批准号:
    261531-2012
  • 财政年份:
    2016
  • 资助金额:
    $ 1.46万
  • 项目类别:
    Discovery Grants Program - Individual
"Search, Opponent Modelling, Cooperation, and State Inference in Complex Imperfect Information Domains."
“复杂不完美信息域中的搜索、对手建模、合作和状态推理。”
  • 批准号:
    261531-2012
  • 财政年份:
    2015
  • 资助金额:
    $ 1.46万
  • 项目类别:
    Discovery Grants Program - Individual
"Search, Opponent Modelling, Cooperation, and State Inference in Complex Imperfect Information Domains."
“复杂不完美信息域中的搜索、对手建模、合作和状态推理。”
  • 批准号:
    261531-2012
  • 财政年份:
    2014
  • 资助金额:
    $ 1.46万
  • 项目类别:
    Discovery Grants Program - Individual
"Search, Opponent Modelling, Cooperation, and State Inference in Complex Imperfect Information Domains."
“复杂不完美信息域中的搜索、对手建模、合作和状态推理。”
  • 批准号:
    261531-2012
  • 财政年份:
    2013
  • 资助金额:
    $ 1.46万
  • 项目类别:
    Discovery Grants Program - Individual
"Search, Opponent Modelling, Cooperation, and State Inference in Complex Imperfect Information Domains."
“复杂不完美信息域中的搜索、对手建模、合作和状态推理。”
  • 批准号:
    261531-2012
  • 财政年份:
    2012
  • 资助金额:
    $ 1.46万
  • 项目类别:
    Discovery Grants Program - Individual

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具有大型动作集和不确定性的决策域中的学习和搜索
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    $ 1.46万
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