Article

An automated negotiation mechanism based on co-evolution and game theory

Authors:

Jen-Hsiang Chen,

Colin Reeves, and

Peter SmithAuthors Info & Claims

SAC '02: Proceedings of the 2002 ACM symposium on Applied computing

March 2002

Pages 63 - 67

https://doi.org/10.1145/508791.508805

Published: 11 March 2002 Publication History

Abstract

The problems associated with current automated negotiation approaches are of little feasibility in practical industry applications. This paper describes a new method that combines a game theory approach and a co-evolutionary approach to support an effective negotiation model for agents to resolve conflict. Under this proposed method, the agents without knowing the other agent's strategies and payoffs, produce an optimised resolution that complies Nash equilibrium and Pareto efficiency concepts. We use a finitely repeated prisoner's dilemma game to demonstrate the proposed method.

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Cited By

Konak AKulturel-Konak S(2022)Regret-Based Nash Equilibrium Sorting Genetic Algorithm for Combinatorial Game Theory Problems with Multiple PlayersEvolutionary Computation10.1162/evco_a_0030830:3(447-478)Online publication date: 1-Sep-2022
https://doi.org/10.1162/evco_a_00308
Konak AKulturel-Konak SSnyder L(2021)Nash equilibrium sorting genetic algorithm for simultaneous competitive maximal covering location with multiple playersEngineering Optimization10.1080/0305215X.2021.195786154:10(1709-1723)Online publication date: 11-Aug-2021
https://doi.org/10.1080/0305215X.2021.1957861
Kiruthika USomasundaram TRaja S(2020)Lifecycle Model of a Negotiation Agent: A Survey of Automated Negotiation TechniquesGroup Decision and Negotiation10.1007/s10726-020-09704-zOnline publication date: 12-Sep-2020
https://doi.org/10.1007/s10726-020-09704-z
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Index Terms

An automated negotiation mechanism based on co-evolution and game theory
1. Computing methodologies
  1. Artificial intelligence
    1. Distributed artificial intelligence
      1. Cooperation and coordination
      2. Multi-agent systems

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Published In

cover image ACM Conferences

SAC '02: Proceedings of the 2002 ACM symposium on Applied computing

March 2002

1200 pages

ISBN:1581134452

DOI:10.1145/508791

Conference Chair:
Gary B. Lamont
Air Force Institute of Technology, USA
,
Program Chairs:
Hisham Haddad
Kennesaw State Univ., USA
,
George Papadopoulos
Univ. of Cyprus, Cyprus
,
Publications Chair:
Brajendra Panda
University of Arkansas, USA

Copyright © 2002 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGAPP: ACM Special Interest Group on Applied Computing

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Association for Computing Machinery

New York, NY, United States

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Published: 11 March 2002

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SAC02: 2002 ACM Symposium on Applied Computing

March 11 - 14, 2002

Madrid, Spain

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Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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Cited By

Konak AKulturel-Konak S(2022)Regret-Based Nash Equilibrium Sorting Genetic Algorithm for Combinatorial Game Theory Problems with Multiple PlayersEvolutionary Computation10.1162/evco_a_0030830:3(447-478)Online publication date: 1-Sep-2022
https://doi.org/10.1162/evco_a_00308
Konak AKulturel-Konak SSnyder L(2021)Nash equilibrium sorting genetic algorithm for simultaneous competitive maximal covering location with multiple playersEngineering Optimization10.1080/0305215X.2021.195786154:10(1709-1723)Online publication date: 11-Aug-2021
https://doi.org/10.1080/0305215X.2021.1957861
Kiruthika USomasundaram TRaja S(2020)Lifecycle Model of a Negotiation Agent: A Survey of Automated Negotiation TechniquesGroup Decision and Negotiation10.1007/s10726-020-09704-zOnline publication date: 12-Sep-2020
https://doi.org/10.1007/s10726-020-09704-z
Baarslag THendrikx MHindriks KJonker C(2016)Learning about the opponent in automated bilateral negotiationAutonomous Agents and Multi-Agent Systems10.1007/s10458-015-9309-130:5(849-898)Online publication date: 1-Sep-2016
https://dl.acm.org/doi/10.1007/s10458-015-9309-1
Lien TYu TYou YPelikan MBranke J(2010)Co-evolution of cooperative strategies under egoismProceedings of the 12th annual conference on Genetic and evolutionary computation10.1145/1830483.1830610(697-704)Online publication date: 7-Jul-2010
https://dl.acm.org/doi/10.1145/1830483.1830610
Hassan ARafie M(2010)A survey of Game Theory using Evolutionary Algorithms2010 International Symposium on Information Technology10.1109/ITSIM.2010.5561648(1319-1325)Online publication date: Jun-2010
https://doi.org/10.1109/ITSIM.2010.5561648
Rossi CAldama LBarrientos A(2009)Simultaneous task subdivision and allocation for teams of heterogeneous robotsProceedings of the 2009 IEEE international conference on Robotics and Automation10.5555/1703435.1703559(764-769)Online publication date: 12-May-2009
https://dl.acm.org/doi/10.5555/1703435.1703559
Rossi CAldama LBarrientos A(2009)Simultaneous task subdivision and allocation for teams of heterogeneous robots2009 IEEE International Conference on Robotics and Automation10.1109/ROBOT.2009.5152299(946-951)Online publication date: May-2009
https://doi.org/10.1109/ROBOT.2009.5152299
Miao Y(2008)Goal oriented interest based negotiation2008 7th IEEE International Conference on Cybernetic Intelligent Systems10.1109/UKRICIS.2008.4798939(1-5)Online publication date: Sep-2008
https://doi.org/10.1109/UKRICIS.2008.4798939
Schmidt SSteele RDillon TChang E(2007)Fuzzy trust evaluation and credibility development in multi-agent systemsApplied Soft Computing10.1016/j.asoc.2006.11.0027:2(492-505)Online publication date: 1-Mar-2007
https://dl.acm.org/doi/10.1016/j.asoc.2006.11.002
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