Abstract
A problem of evaluating the non-cooperative game model is considered in the paper. The evaluation is understood in the sense of obtaining the game payoff matrices whose entries are single-point values. Experts participating in the estimation procedure make their judgments on all the game situations for every player. A form of expert estimations is suggested. The form is of binary type, wherein the expert’s judgment is either 1 or 0. This type is the easiest to be implemented in social networks. For most social networks, 1 can be a “like” (the currently evaluated situation is advantageous), and 0 is a “dislike” (disadvantageous). A method of processing expert estimations is substantiated. Two requirements are provided for obtaining disambiguous payoff averages along with the clustered payoff matrices.
Highlights
An ambiguous problem in the game theory and decision making is numerical evaluation of situations [1], [2]
The only theorised way is to use binary relations [6], [7]. This leads to the simplest pairwise comparisons, where experts are required [8], [9]
Methods of processing expert estimations are determined by their form and structure
Summary
An ambiguous problem in the game theory and decision making is numerical evaluation of situations [1], [2]. A situation, in those fields, is a list of pure strategies (decisions and states [3], [4]). There are no theoretic ways to evaluate all the set of pure strategy situations and to get payoff matrices outright [2], [5]. The only theorised way is to use binary relations [6], [7]. This leads to the simplest pairwise comparisons, where experts are required [8], [9]. The question is how many experts should be invoked and what method should be applied to process the expert estimations
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