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A Greedy Coordinate Descent Algorithm for High-Dimensional Nonlinear Negotiation

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Recent Advances in Agent-based Complex Automated Negotiation

Part of the book series: Studies in Computational Intelligence ((SCI,volume 638))

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Abstract

Automated negotiation is a rapidly growing topic in the field of artificial intelligence. Most of the research has been dedicated to linear preferences. Approaching real life negotiations requires more realistic preference profiles to be taken into account. To address this need, nonlinear high-dimensional domains with interdependent issues were introduced. They have however posed a struggle for automated negotiation agents. The difficulty is that fast, linear models can no longer be used in such domains, and there is no time to consider all possible bids in huge spaces. This paper proposes Group2Agent (G2A), an agent that copes with these complex domains and tries to find high Social Welfare outcomes. G2A uses a variant of the Greedy Coordinate Descent (GCD) algorithm, which can scale linearly with the number of issues and is shown to be effective in locating a meaningful middle ground between negotiating parties. Our results show that G2A reaches an average Social Welfare of 1.79, being only 0.03 below the optimal Social Welfare solution and found the optimal solution itself 3 out of 25 times on pre-competition domains. In conclusion, G2A performs among the top ranking agents when it comes to Social Welfare. Furthermore its search algorithm, GCD, scales better than algorithms such as Simulated Annealing used in other agents.

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Acknowledgments

We thank Dr. C.M. Jonker and Dr. K.V. Hindriks for introducing us to the field of negotiation and Dr. R. Aydogan and Dr. T. Baarslag for inviting us to the ANAC 2014 competition and supporting us. We also would like to thank S. Rekha for being a team member designing the original linear agent.

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Authors and Affiliations

  1. Delft University of Technology, Mekelweg 4, Delft, The Netherlands

    Bálint Szöllősi-Nagy, David Festen & Marta M. Skarżyńska

Authors
  1. Bálint Szöllősi-Nagy
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  2. David Festen
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  3. Marta M. Skarżyńska
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Corresponding author

Correspondence to Bálint Szöllősi-Nagy .

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Editors and Affiliations

  1. Hamamatsu, Shizuoka, Japan

    Naoki Fukuta

  2. Nagoya Institute of Technology, Nagoya, Japan

    Takayuki Ito

  3. School of Computer Science, University of Wollongong, Wollongong, New South Wales, Australia

    Minjie Zhang

  4. Tokyo University of Agriculture and, Tokyo, Japan

    Katsuhide Fujita

  5. Institute of Sensors, Signals, Heriot-Watt University, Riccarton, United Kingdom

    Valentin Robu

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Szöllősi-Nagy, B., Festen, D., Skarżyńska, M.M. (2016). A Greedy Coordinate Descent Algorithm for High-Dimensional Nonlinear Negotiation. In: Fukuta, N., Ito, T., Zhang, M., Fujita, K., Robu, V. (eds) Recent Advances in Agent-based Complex Automated Negotiation. Studies in Computational Intelligence, vol 638. Springer, Cham. https://doi.org/10.1007/978-3-319-30307-9_17

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  • DOI: https://doi.org/10.1007/978-3-319-30307-9_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-30305-5

  • Online ISBN: 978-3-319-30307-9

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