Peter Stone's Selected Publications

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TacTex'13: A Champion Adaptive Power Trading Agent

Daniel Urieli and Peter Stone. TacTex'13: A Champion Adaptive Power Trading Agent. In Proceedings of the Twenty-Eighth Conference on Artificial Intelligence (AAAI 2014), July 2014.

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Abstract

Sustainable energy systems of the future will no longer be able to rely on the current paradigm that energy supply follows demand. Many of the renewable energy resources do not produce power on demand, and therefore there is a need for new market structures that motivate sustainable behaviors by participants. The Power Trading Agent Competition (Power TAC) is a new annual competition that focuses on the design and operation of future retail power markets, specifically in smart grid environments with renewable energy production, smart metering, and autonomous agents acting on behalf of customers and retailers. It uses a rich, open-source simulation platform that is based on real-world data and state-of-the-art customer models. Its purpose is to help researchers understand the dynamics of customer and retailer decision-making, as well as the robustness of proposed market designs. This paper introduces TacTex'13, the champion agent from the inaugural competition in 2013. TacTex'13 learns and adapts to the environment in which it operates, by heavily relying on reinforcement learning and prediction methods. This paper describes the constituent components of TacTex'13 and examines its success through analysis of competition results and subsequent controlled experiments.

BibTeX Entry

@InProceedings{AAAI14-urieli,
  author = {Daniel Urieli and Peter Stone},
  title = {TacTex'13: A Champion Adaptive Power Trading Agent},
  booktitle = {Proceedings of the Twenty-Eighth Conference on Artificial Intelligence (AAAI 2014)},
  location = {Quebec City, Quebec, Canada},
  month = {July},
  year = {2014},
  abstract = {
    Sustainable energy systems of the future will no longer be able to
    rely on the current paradigm that energy supply follows demand. Many
    of the renewable energy resources do not produce power on demand, and
    therefore there is a need for new market structures that motivate
    sustainable behaviors by participants.  The Power Trading Agent
    Competition (Power TAC) is a new annual competition that focuses on
    the design and operation of future retail power markets, specifically
    in smart grid environments with renewable energy production, smart
    metering, and autonomous agents acting on behalf of customers and
    retailers. It uses a rich, open-source simulation platform that is
    based on real-world data and state-of-the-art customer models. Its
    purpose is to help researchers understand the dynamics of customer and
    retailer decision-making, as well as the robustness of proposed market
    designs. This paper introduces TacTex'13, the champion agent from
    the inaugural competition in 2013. TacTex'13 learns and adapts to the
    environment in which it operates, by heavily relying on
    reinforcement learning and prediction methods. 
    This paper describes the
    constituent components of TacTex'13 and examines its success 
    through analysis of competition results and subsequent
    controlled experiments.
  },
} 

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