Abstract
Automated negotiations require a more elaborated dialogue where agents would explain offer rejections in a general and vague way. We propose to represent the disappointment about an offer through fuzzy logic. Specifically we study two alternatives: a piece-wise fuzzy set or a linguistic label applied to each attribute of the offer. These alternatives are evaluated comparing the performance of both types of counter-offers with a classical approach based on linear programming. Therefore, the media of negotiation length, benefits and percentage of agreements allow us to conclude the accuracy of the alternatives proposed.
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Carbo, J., Ledezma A.,: A machine learning based evaluation of a negotiation involving fuzzy counter-offers. In Procs. Int. Conf. on Atlantic Web Intelligence (2003).
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Carbo, J., Molina, J.M., Dávila, J. (2003). Reaching Agreements through Fuzzy Counter-Offers. In: Lovelle, J.M.C., Rodríguez, B.M.G., Gayo, J.E.L., del Puerto Paule Ruiz, M., Aguilar, L.J. (eds) Web Engineering. ICWE 2003. Lecture Notes in Computer Science, vol 2722. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45068-8_16
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DOI: https://doi.org/10.1007/3-540-45068-8_16
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