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A Quantitative Concession-Based Classification Method of Bidding Strategies

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Exploring the Strategy Space of Negotiating Agents

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Abstract

In this chapter, we cover the last agent strategy component of the BOA architecture of Chap. 3, namely the bidding strategy; i.e., the strategy component that decides the concessions to be made during the negotiation. Every negotiator needs to make concessions to successfully reach an agreement, and the willingness to do so depends in large part on the opponent. A concession by the opponent may be reciprocated, but the negotiation process may also be frustrated if the opponent does not concede at all. This process of concession making is a central theme in many automated negotiation strategies. In this chapter, we present a quantitative classification method of negotiation strategies that measures the willingness of an agent to concede against different types of opponents. We classify some well-known negotiating strategies with respect to their concession behavior, including the ANAC agents we described in Appendix B. We show that our technique makes it easy to identify the main characteristics of negotiation agents, and that it can be used to group negotiation strategies into four categories with common negotiation characteristics, namely Inverter, Conceder, Competitor, and Matcher. We are able to conclude, among other things, that different kinds of opponents call for adopting a different negotiation orientation. Our analysis allows us to highlight several interesting insights for the broader automated negotiation community. In particular, we show that the most adaptive negotiation strategies are not necessarily the ones that win the competition.

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Notes

  1. 1.

    Note that an optimal outcome \(\overline{\omega }_A\) is not necessarily unique, but typical domains (including those considered in ANAC and hence, in this chapter) all have unique optimal outcomes for both players, so that the full yield utility is well-defined.

  2. 2.

    The Random Walker strategy is also known as the Zero Intelligence strategy [6].

References

  1. Baarslag T, Fujita K, Gerding EH, Hindriks KV, Ito T, Jennings NR, Jonker CM, Kraus S, Lin R, Robu V, Williams CR (2013) Evaluating practical negotiating agents: Results and analysis of the 2011 international competition. Artif Intell 198:73–103

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  2. Baarslag T, Hindriks KV, Jonker CM (2011) Towards a quantitative concession-based classification method of negotiation strategies. In: Kinny D, Yung-jen Hsu J, Governatori G, Ghose AK (eds) Agents in principle, agents in practice, lecture notes in computer science, vol 7047. Springer, Berlin, Heidelberg, pp 143–158

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This chapter is based on the following publications: [1, 2]

Tim Baarslag, Koen V. Hindriks, and Catholijn M. Jonker. Towards a quantitative concession-based classication method of negotiation strategies. In David Kinny, Jane Yung-jen Hsu, Guido Governatori, and Aditya K. Ghose, editors, Agents in Principle, Agents in Practice, volume 7047 of Lecture Notes in Computer Science, pages 143–158, Berlin, Heidelberg, 2011. Springer Berlin Heidelberg

Tim Baarslag, Katsuhide Fujita, Enrico H. Gerding, Koen V. Hindriks, Takayuki Ito, Nicholas R. Jennings, Catholijn M. Jonker, Sarit Kraus, Raz Lin, Valentin Robu, and Colin R. Williams. Evaluating practical negotiating agents: Results and analysis of the 2011 international competition. Articial Intelligence, 198:73–103, May 2013

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Baarslag, T. (2016). A Quantitative Concession-Based Classification Method of Bidding Strategies. In: Exploring the Strategy Space of Negotiating Agents. Springer Theses. Springer, Cham. https://doi.org/10.1007/978-3-319-28243-5_8

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  • DOI: https://doi.org/10.1007/978-3-319-28243-5_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-28242-8

  • Online ISBN: 978-3-319-28243-5

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