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317 Research products, page 1 of 32

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  • Other research product . 1910
    Open Access English
    Publisher: The Cowichan Leader
    Country: Canada

    https://viurrspace.ca/bitstream/handle/10613/7023/July07-1910.pdf?sequence=2

  • Open Access English
    Publisher: Nanaimo Free Press
    Country: Canada

    https://viurrspace.ca/bitstream/handle/10613/19025/Dec26-1874.pdf?sequence=2&isAllowed=y

  • Open Access English
    Publisher: Nanaimo Free Press
    Country: Canada

    https://viurrspace.ca/bitstream/handle/10613/21979/Feb26-1879.pdf?sequence=2

  • Open Access English
    Publisher: Nanaimo Free Press
    Country: Canada

    https://viurrspace.ca/bitstream/handle/10613/13279/Feb20-1905.pdf?sequence=2

  • Open Access English
    Publisher: Nanaimo Free Press
    Country: Canada

    https://viurrspace.ca/bitstream/handle/10613/19845/Aug29-1894.pdf?sequence=2

  • Open Access English
    Publisher: Nanaimo Free Press
    Country: Canada

    https://viurrspace.ca/bitstream/handle/10613/19164/Nov27-1875.pdf?sequence=2&isAllowed=y

  • Open Access English
    Publisher: Nanaimo Free Press
    Country: Canada

    https://viurrspace.ca/bitstream/handle/10613/21933/Feb27-1878.pdf?sequence=2

  • Other research product . 2014
    Open Access English
    Authors: 
    Xin Jiang, Albert; Soriano Marcolino, Leandro; Procaccia, Ariel D.; Sandholm, Tuomas; Shah, Nisarg; Tambe, Milind;
    Country: United Kingdom
    Project: NSF | ICES: Small: Computationa... (1215883), NSF | CAREER: A Broad Synthesis... (1350598)

    We investigate the power of voting among diverse, randomized software agents. With teams of computer Go agents in mind, we develop a novel theoretical model of two-stage noisy voting that builds on recent work in machine learning. This model allows us to reason about a collection of agents with different biases (determined by the first-stage noise models), which, furthermore, apply randomized algorithms to evaluate alternatives and produce votes (captured by the second-stage noise models). We analytically demonstrate that a uniform team, consisting of multiple instances of any single agent, must make a significant number of mistakes, whereas a diverse team converges to perfection as the number of agents grows. Our experiments, which pit teams of computer Go agents against strong agents, provide evidence for the effectiveness of voting when agents are diverse.

  • Open Access English
    Publisher: Nanaimo Free Press
    Country: Canada

    https://viurrspace.ca/bitstream/handle/10613/8934/Dec26-1908.pdf?sequence=2

  • Open Access English
    Publisher: Nanaimo Free Press
    Country: Canada

    https://viurrspace.ca/bitstream/handle/10613/18481/Jun19-1912.pdf?sequence=2&isAllowed=y

search
Include:
The following results are related to Canada. Are you interested to view more results? Visit OpenAIRE - Explore.
317 Research products, page 1 of 32
  • Other research product . 1910
    Open Access English
    Publisher: The Cowichan Leader
    Country: Canada

    https://viurrspace.ca/bitstream/handle/10613/7023/July07-1910.pdf?sequence=2

  • Open Access English
    Publisher: Nanaimo Free Press
    Country: Canada

    https://viurrspace.ca/bitstream/handle/10613/19025/Dec26-1874.pdf?sequence=2&isAllowed=y

  • Open Access English
    Publisher: Nanaimo Free Press
    Country: Canada

    https://viurrspace.ca/bitstream/handle/10613/21979/Feb26-1879.pdf?sequence=2

  • Open Access English
    Publisher: Nanaimo Free Press
    Country: Canada

    https://viurrspace.ca/bitstream/handle/10613/13279/Feb20-1905.pdf?sequence=2

  • Open Access English
    Publisher: Nanaimo Free Press
    Country: Canada

    https://viurrspace.ca/bitstream/handle/10613/19845/Aug29-1894.pdf?sequence=2

  • Open Access English
    Publisher: Nanaimo Free Press
    Country: Canada

    https://viurrspace.ca/bitstream/handle/10613/19164/Nov27-1875.pdf?sequence=2&isAllowed=y

  • Open Access English
    Publisher: Nanaimo Free Press
    Country: Canada

    https://viurrspace.ca/bitstream/handle/10613/21933/Feb27-1878.pdf?sequence=2

  • Other research product . 2014
    Open Access English
    Authors: 
    Xin Jiang, Albert; Soriano Marcolino, Leandro; Procaccia, Ariel D.; Sandholm, Tuomas; Shah, Nisarg; Tambe, Milind;
    Country: United Kingdom
    Project: NSF | ICES: Small: Computationa... (1215883), NSF | CAREER: A Broad Synthesis... (1350598)

    We investigate the power of voting among diverse, randomized software agents. With teams of computer Go agents in mind, we develop a novel theoretical model of two-stage noisy voting that builds on recent work in machine learning. This model allows us to reason about a collection of agents with different biases (determined by the first-stage noise models), which, furthermore, apply randomized algorithms to evaluate alternatives and produce votes (captured by the second-stage noise models). We analytically demonstrate that a uniform team, consisting of multiple instances of any single agent, must make a significant number of mistakes, whereas a diverse team converges to perfection as the number of agents grows. Our experiments, which pit teams of computer Go agents against strong agents, provide evidence for the effectiveness of voting when agents are diverse.

  • Open Access English
    Publisher: Nanaimo Free Press
    Country: Canada

    https://viurrspace.ca/bitstream/handle/10613/8934/Dec26-1908.pdf?sequence=2

  • Open Access English
    Publisher: Nanaimo Free Press
    Country: Canada

    https://viurrspace.ca/bitstream/handle/10613/18481/Jun19-1912.pdf?sequence=2&isAllowed=y