Abstract
One of the most recent mathematical models for negotiation is the Compensatory Negotiation Solution by Knowledge Engineering (CNSKE). In this model a logic system called Compensatory Fuzzy Logic was used, which is more adequate to solve problems of decision making than the classical one probabilistic fuzzy logic system. The idempotency axiom of this system and the continuity of the operators allow the truth-values of the membership function to have a cardinal and not exclusively ordinal semantic meaning. On the other hand, continuity also makes ‘sensible’ the truth-values of the predicates. The aim of this paper is to illustrate the advantages of the CNSKE over other approaches in Game Theory. To show these advantages, some case studies are analyzed, consisting on the solution of three problems in which CNSKE is applied in economic and politic cases of negotiation, and compared with other alternative approaches.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Alonso-Meijide JM, Fiestras-Janeiro MG (2002) Modification of the Banzhaf value for games with a coalition structure. Ann Oper Res 109(1–4):213–227
Bazerman M, Neale M (1992) Negotiating rationally. The Free Press, New York
Buchanan B, Shortliffe E (1984) Knowledge engineering. In: Buchanan BG, Shortliffe EH (eds) Rule-based expert systems—the MYCIN experiments of the Stanford Heuristic Programming Project. Addison-Wesley, Massachusetts, pp 147–158
Casagrande T, Ranganathan N (2015) GTFUZZ: a novel algorithm for robust dynamic power optimization via gate sizing with fuzzy games. In: Proceedings of the 2015 design, automation and test in Europe conference & exhibition (pp. 677–682). EDA consortium
Cobanli O (2014) Central Asian gas in Eurasian power game. Energy Policy 68:348–370
Dubois D, Esteva F, Godo L, Prade H (2007) Fuzzy-set based logic- an history -oriented presentation of their main developments. In: Gabbay D, Woods J (eds) Handbook of the history of logic. Elsevier, B.V., Amsterdam, pp 325–449
Espín R, Fernández E, Mazcorro G, Lecich M (2007) A fuzzy approach to cooperative n-person games. Eur J Oper Res 176(3):1735–1751
Espín R, Fernández E, González E (2011) A logic system for reasoning and decision taking: the geometric mean based compensatory logic (in spanish). Revista Investigación Operacional 32(3):230–245
Espín R, Fernández E, González E (2014) Compensatory fuzzy logic: a frame for reasoning and modeling preference knowledge in intelligent systems. In: Espin R, Bello R, Marx J (eds) Soft computing for business intelligence. Springer, Berlin, pp 3–23
Fisher R, Ury W (1983) Getting to yes: negotiating an agreement without giving in. Penguin Books, New York
Fitzgerald ME, Ross AM (2015) Effects of enhanced multi-party tradespace visualization on a two-person negotiation. Procedia Comput Sci 44:466–475
French S (1986) Decision theory: an introduction to the mathematics of rationality. Halsted Press, New York
González E, Espín R, Mazcorro G (2012) Fuzzy negotiation solutions of N-person cooperative games by knowledge engineering in bargaining. Group Decis Negot 21(2):133–152
González E, Espín R, Mazcorro G, Espín R (2013a) Existence and uniqueness of two fuzzy solutions to cooperative games. In: Fourth international workshop on knowledge discovery, knowledge management and decision support. Atlantis Press, pp 64–70
González E, Espín R, Mazcorro G, Muñoz S (2013b) Rationality of two fuzzy negotiation solutions by knowledge engineering to n-person cooperative games. In: Fourth international workshop on knowledge discovery, knowledge management and decision support. Atlantis Press, pp 55–63
Guajardo M, Jörnsten K (2015) Common mistakes in computing the nucleolus. Eur J Oper Res 241(3):931–935
Hanscomb S (2015) Assessment and the self: academic practice and character attributes. J Learn Dev Higher Educ 2015(8)
Hart S (1997a) Classical cooperative theory I: core-like concepts. In: Hart S, Mas-Colell A (eds) Cooperation: game theoretic approaches. Springer, New York, pp 35–42
Hart S (1997b) Classical cooperative theory II: value-like solutions. In: Hart S, Mas-Colell A (eds) Cooperation: game theoretic approaches. Springer, New York, pp 43–49
Hiller T (2015) The importance of players in teams of the German Bundesliga in the season 2012/2013-a cooperative game theory approach. Appl Econ Lett 22(4):324–329
Kahneman D, Tversky A (1979) Prospect theory: an analysis of decision under risk. Econometrica 47(2):263–291
Korobkin R (2008) Against integrative bargaining. Case West Reserve Law Rev 58(4):1323–1342
Leng M, Parlar M, Zhang D (2014) Cooperative game analysis of retail space-exchange problems. Eur J Oper Res 232(2):393–404
Lewicki R, Weiss S, Lewin D (1992) Models of conflict, negotiation and third party intervention: a review and synthesis. J Org Behav 13(3):209–252
Menkel-Meadow C (1993) Lawyer negotiations: theories and realities what we learn from mediation. Mod Law Rev Limit 56(3):361–379
Mircică N (2014) Constructive communication in effective negotiation. Anal Metaphys 13:64–72
Mizumoto M (1989) Pictorial representations of fuzzy connectives: part II. Cases of compensatory operators and self-dual operators. Fuzzy Sets Syst 32(1):45–79
Newton J, Sawa R (2015) A one-shot deviation principle for stability in matching problems. J Econ Theory 157:1–27
Peneva V, Popchev I (2006) Models for weighted aggregation of fuzzy relations to multicriteria decision making problems. Cybern Inform Technol 6(3):3–18
Rahaman M, Ahmad R (2015) Fuzzy vector equilibrium problem. Iran J Fuzzy Syst 12(1):115–122
Raiffa H (1982) The art and science of negotiation. Harvard University Press, London
Raiffa H (1991) Contributions of applied systems analysis to international negotiation. In: Kremenyuk V (ed) International negotiation. Jossey-Bass, San Francisco, pp 5–21
Tao Z, Liu X, Chen H, Chen Z (2015) Group decision making with fuzzy linguistic preference relations via cooperative games method. Comput Indust Eng 83:184–192
Thomas L (1984) Games, theory and applications. Wiley, New York
Winter E (2002) The shapley value. In: Aumann RJ, Hart S (eds) Handbook of game theory with economic applications. Elsevier, B.V., Amsterdam, pp 2025–2054
Zadeh L (2002) From computing with numbers to computing with words—from manipulation of measurements to manipulation of perceptions. Int J Appl Math Comput Sci 12(3):307–324
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
González, E., Alejandro Espín, R. & Fernández, E. Negotiation Based on Fuzzy Logic and Knowledge Engineering: Some Case Studies. Group Decis Negot 25, 373–397 (2016). https://doi.org/10.1007/s10726-015-9446-6
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10726-015-9446-6