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An Efficient Negotiation Protocol to Achieve Socially Optimal Allocation

  • Conference paper

Part of the Lecture Notes in Computer Science book series (LNAI,volume 7455)

Abstract

Negotiation-based resource allocation among agents is an important topic in multi-agent system research and it can be applied in various practical domains including network bandwidth allocation, robotics and grid computing. However, it is quite challenging to achieve efficient negotiation due to the huge space of all possible deals. A number of negotiation protocols have been proposed to guide the agents to reach desirable allocations over resources. However, previous work puts too much constraints on the negotiation environment and thus limits its applicability. To address this limitation, we present an efficient protocol within a more general negotiation framework, which can lead agents to achieve socially optimal allocation. We theoretically prove that the final allocation is guaranteed to be socially optimal provided that the agents are altruistic-individually rational. Besides, extensive simulation results show that the complexities of the negotiation process are greatly reduced under our protocol from both communication and computational aspects.

Keywords

  • Utility Function
  • Leaf Node
  • Child Node
  • Optimal Allocation
  • Negotiation Process

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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© 2012 Springer-Verlag Berlin Heidelberg

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Hao, J., Leung, Hf. (2012). An Efficient Negotiation Protocol to Achieve Socially Optimal Allocation. In: Rahwan, I., Wobcke, W., Sen, S., Sugawara, T. (eds) PRIMA 2012: Principles and Practice of Multi-Agent Systems. PRIMA 2012. Lecture Notes in Computer Science(), vol 7455. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32729-2_4

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  • DOI: https://doi.org/10.1007/978-3-642-32729-2_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32728-5

  • Online ISBN: 978-3-642-32729-2

  • eBook Packages: Computer ScienceComputer Science (R0)