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Mathematical models of two‐party negotiations
Author(s) -
England J. Lynn
Publication year - 1973
Publication title -
behavioral science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.371
H-Index - 45
eISSN - 1099-1743
pISSN - 0005-7940
DOI - 10.1002/bs.3830180306
Subject(s) - markov chain , negotiation , computer science , markov process , mathematical economics , process (computing) , markov model , operator (biology) , econometrics , mathematical model , artificial intelligence , operations research , management science , machine learning , economics , mathematics , statistics , political science , law , biochemistry , chemistry , repressor , transcription factor , gene , operating system
The present paper describes a pair of mathematical models of two‐party bargaining. One model is a Markov process with inputs. The other is a two‐party version of the Bush‐Mosteller linear operator learning model. The adequacy of the two models is examined in a computer controlled experiment. The Markov chain model fails to predict the extinction of cooperation encountered in certain experimental groups. It does adequately predict the trial of agreement. The learning model describes the proportion of cooperative responses quite accurately in all experimental groups. It is not as accurate in predicting agreement as the Markov process.