Publications

Résumé This chapter considers potential games, where agents play, each period, Nash worthwhile moves in alternation, such that their unilateral motivation to change rather than to stay, other players being supposed to stay, are high enough with respect to their resistance to change rather than to stay. This defines a generalized proximal alternating linearized algorithm, where resistance to change plays a major role, perturbation terms of alternating proximal algorithms being seen as the disutilities of net costs of moving.
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Résumé This paper concerns applications of variational analysis to some local aspects of behavioral science modeling by developing an effective variational rationality approach to these and related issues. Our main attention is paid to local stationary traps, which reflect such local equilibrium and the like positions in behavioral science models that are not worthwhile to quit. We establish constructive linear optimistic evaluations of local stationary traps by using generalized differential tools of variational analysis that involve subgradients and normals for nonsmooth and nonconvex objects as well as variational and extremal principles.
Mots clés Variational rationality, Applications to behavioral sciences, Variational and extremal principles, Normals, Sub-gradients, Worthwhile moves, Optimization, Variational analysis
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