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2017 | OriginalPaper | Buchkapitel

Rethinking Frequency Opponent Modeling in Automated Negotiation

verfasst von : Okan Tunalı, Reyhan Aydoğan, Victor Sanchez-Anguix

Erschienen in: PRIMA 2017: Principles and Practice of Multi-Agent Systems

Verlag: Springer International Publishing

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Abstract

Frequency opponent modeling is one of the most widely used opponent modeling techniques in automated negotiation, due to its simplicity and its good performance. In fact, it outperforms even more complex mechanisms like Bayesian models. Nevertheless, the classical frequency model does not come without its own assumptions, some of which may not always hold in many realistic settings. This paper advances the state of the art in opponent modeling in automated negotiation by introducing a novel frequency opponent modeling mechanism, which soothes some of the assumptions introduced by classical frequency approaches. The experiments show that our proposed approach outperforms the classic frequency model in terms of evaluation of the outcome space, estimation of the Pareto frontier, and accuracy of both issue value evaluation estimation and issue weight estimation.

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Vorheriges Kapitel Crafting Ontology Alignments from Scratch Through Agent Communication

Nächstes Kapitel Optimizing Affine Maximizer Auctions via Linear Programming: An Application to Revenue Maximizing Mechanism Design for Zero-Day Exploits Markets

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2 models \(\times \) 5 opponents \(\times \) 8 domains \(\times \) 2 profiles \(\times \) 20 repetitions.

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Titel: Rethinking Frequency Opponent Modeling in Automated Negotiation
verfasst von: Okan Tunalı
Reyhan Aydoğan
Victor Sanchez-Anguix
Verlag: Springer International Publishing
Buch: PRIMA 2017: Principles and Practice of Multi-Agent Systems
Print ISBN: 978-3-319-69130-5

Electronic ISBN: 978-3-319-69131-2

Copyright-Jahr: 2017
DOI: https://doi.org/10.1007/978-3-319-69131-2_16

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