Multi-sided Böhm-Bawerk assignment markets: the core

[cat] En aquest treball introduïm la classe de "multi-sided Böhm-Bawerk assignment games", que generalitza la coneguda classe de jocs d’assignació de Böhm-Bawerk bilaterals a situacions amb un nombre arbitrari de sectors. Trobem els extrems del core de qualsevol multi-sided Böhm-Bawerk assignment game a partir d’un joc convex definit en el conjunt de sectors enlloc del conjunt de venedors i compradors. Addicionalment estudiem quan el core d’aquests jocs d’assignació és estable en el sentit de von Neumann-Morgenstern.

Multi-sided Böhm-Bawerk assignment markets: the core

[cat] En aquest treball introduïm la classe de "multi-sided Böhm-Bawerk assignment games", que generalitza la coneguda classe de jocs d’assignació de Böhm-Bawerk bilaterals a situacions amb un nombre arbitrari de sectors. Trobem els extrems del core de qualsevol multi-sided Böhm-Bawerk assignment game a partir d’un joc convex definit en el conjunt de sectors enlloc del conjunt de venedors i compradors. Addicionalment estudiem quan el core d’aquests jocs d’assignació és estable en el sentit de von Neumann-Morgenstern.

Statistical mechanics of multi-edge networks

Statistical properties of binary complex networks are well understood and recently many attempts have been made to extend this knowledge to weighted ones. There are, however, subtle yet important considerations to be made regarding the nature of the weights used in this generalization. Weights can be either continuous or discrete magnitudes, and in the latter case, they can additionally have undistinguishable or distinguishable nature. This fact has not been addressed in the literature insofar and has deep implications on the network statistics. In this work we face this problem introducing multiedge networks as graphs where multiple (distinguishable) connections between nodes are considered. We develop a statistical mechanics framework where it is possible to get information about the most relevant observables given a large spectrum of linear and nonlinear constraints including those depending both on the number of multiedges per link and their binary projection. The latter case is particularly interesting as we show that binary projections can be understood from multiedge processes. The implications of these results are important as many real-agent-based problems mapped onto graphs require this treatment for a proper characterization of their collective behavior.