1993
DOI: 10.1007/bf01783413
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On the structure of the set of perfect equilibria in bimatrix games

Abstract: On the structure of the set of perfect equilibria in bimatrix games Borm, Peter; Jansen, M.J.M.; Potters, J.A.M.; Tijs, S.H.

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Cited by 13 publications
(15 citation statements)
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“…(x 1 , x 2 ) ∈ T and (y 1 , y 2 ) ∈ T imply that (x 1 , y 2 ) ∈ T and (y 1 , x 2 ) ∈ T . A Nash subset T is called maximal if it is not properly contained in another Nash subset (Jansen [6]). Any extreme equilibrium is an extreme point of one of these maximal Nash subsets.…”
Section: Enumeration Of All Maximal Nash Subsetsmentioning
confidence: 99%
See 2 more Smart Citations
“…(x 1 , x 2 ) ∈ T and (y 1 , y 2 ) ∈ T imply that (x 1 , y 2 ) ∈ T and (y 1 , x 2 ) ∈ T . A Nash subset T is called maximal if it is not properly contained in another Nash subset (Jansen [6]). Any extreme equilibrium is an extreme point of one of these maximal Nash subsets.…”
Section: Enumeration Of All Maximal Nash Subsetsmentioning
confidence: 99%
“…We then use exact arithmetics as in [3] to determine the rank of the corresponding matrices A(T ) and B(T ). Example 2.2 For the bimatrix game taken from Borm et al [6], we have determined the dimensions of the six maximal Nash subsets found (Table 2).…”
Section: Maximal Nash Subset Geometry and Dimensionmentioning
confidence: 99%
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“…Her constructive proof generates a correspondence whose fixed points are precisely the perfect equilibria of a given finite game. For bimatrix games, Borm et al [22] described a maximal Selten subset as a set of interchangeable perfect equilibria. Each maximal Selten subset is a subset of a maximal Nash subset and each extreme point of a maximal Selten subset corresponds to an extreme perfect equilibrium.…”
Section: Motivation Decision Makers Confronted To Multiplementioning
confidence: 99%
“…A Nash subset is called maximal if it is not properly contained in another Nash subset [22]. Enumeration of all maximal Nash subsets can be achieved using an algorithm for the enumeration of all maximal cliques of a graph [26].…”
Section: (5)mentioning
confidence: 99%