Meaningful and Meaningless Solutions for Cooperative N-person Games

Game values often represent data that can be measured in morethan one acceptable way (e.g. monetary amounts). We point out thatin such a case a statement about cooperative n-person game modelmight be "meaningless" in the sense that its truth or falsity depends onthe choice of an acceptable way to measure game values. In particularwe analyze statements about solution concepts such as the core, stablesets, the nucleolus, the Shapley value (and its generalizations).Keywords: Cooperative n-person Games, Measurement, SensitivityAnalysis

Trust and corruption: escalating social practices?

Escalating social practices spread dynamically, as they take hold. They are selffulfilling and contagious. This article examines two central social practices, trust and corruption, which may be characterized as alternative economic lubricants. Corruption can be a considerable instrument of flexibility while trust may be an alternative to vigilance (or a collective regime of sanctions). Rational equilibrium explanations and psychological accounts of trust and corruption are rejected in favour of a model open to multiple feed-backs. Although there can be too much trust and too little corruption, and (unsurprisingly) too little trust and too much corruption, a state is unattainable in which these forces are in balance. Practices of trust alone can form stable equilibria, but it is claimed that such states are undesirable for economic and moral reasons. By contrast, practices of corruption are inherently unstable. Implications for strategies of control in organizational relations are drawn

Strategic Power Revisited

Traditional power indices ignore preferences and strategic interaction. Equilibrium analysis of particular non-cooperative decision procedures is unsuitable for normative analysis and assumes typically unavailable information. These points drive a lingering debate about the right approach to power analysis. A unified framework that works both sides of the street is developed here. It rests on a notion of a posteriori power which formalizes players' marginal impact to outcomes in cooperative and non-cooperative games, for strategic interaction and purely random behaviour. Taking expectations with respect to preferences, actions, and procedures then defines a meaningful a priori measure. Established indices turn out to be special cases.power indices, spatial voting, equilibrium analysis, decision procedures

Nash Bargaining Solution with Coalitions and The Joint Bargaining Paradox

We propose a solution for bargaining problems where coalitions are bargainers. The solution generalizes the Nash solution and allows one to interpret a coalition as an institutional player whose preferences are obtained by aggregating the preferences of the individual members. One implication of our solution is that forming a coalition is unprofitable in pure-bargaining situations (the joint-bargaining paradox). We show, however, that forming a coalition can be profitable in a non-pure bargaining situation. ZUSAMMENFASSUNG - (Die Nash Verhandlungslösung mit Koalitionen und Harsanyi's Verhandlungsparadox) In der vorliegenden Arbeit schlagen wir ein Lösungskonzept für Verhandlungsspiele vor, bei denen die verhandelnden Parteien aus Koalitionen von Individuen bestehen können. Unser Lösungskonzept basiert auf einer Verallgemeinerung der Nash-Verhandlungslösung. Nach unserem Lösungskonzept kann eine Koalition als ein institutioneller Spieler aufgefasst werden, dessen Präferenzordnung auf einer Aggregierung der Präferenzen seiner Mitglieder basiert. Eine Implikation unserer Verhandlungslösung ist, dass Koalitionen in "reinen Verhandlungsspielen" nicht im Interesse der Individuen sind. In "nicht reinen Verhandlungsspielen" hingegen können Koalitionen durchaus vorteilhaft seien.Nash Bargaining Solution, Coalition, Joint-Bargaining Paradox

Voting Power in the EU Council of Ministers and Fair Decision Making in Distributive Politics

We analyze and evaluate the different decision rules describing the Council of Ministers of the EU starting from 1958 up to date. All the existing studies use the Banzhaf index (for binary voting) or the Shapley-Shubik index (for distributive politics). We argue that the nucleolus can be considered an appropriate power measure in distributive situations and an alternative to the Shapley-Shubik index. We then calculate the nucleolus and compare the results of our calculations with the conventional measures. In the second part, we analyze the power of the European citizens as measured by the nucleolus under the egalitarian criterion proposed by Felsenthal and Machover (1998), and characterize the first best situation. Based on these results we propose a methodology for the design of the optimal (fair) decision rules. We perform the optimization exercise for the earlier stages of the EU within a restricted domain of voting rules, and conclude that Germany should receive more than the other three large countries under the optimal voting rule.

Mean Field Games and Applications.

This text is inspired from a “Cours Bachelier” held in January 2009 and taught by Jean-Michel Lasry. This course was based upon the articles of the three authors and upon unpublished materials they developed. Proofs were not presented during the conferences and are now available. So are some issues that were only rapidly tackled during class.Mean Field Games;

Neural Coding of Cooperative vs. Affective Human Interactions: 150 ms to Code the Action's Purpose

The timing and neural processing of the understanding of social interactions was investigated by presenting scenes in which 2 people performed cooperative or affective actions. While the role of the human mirror neuron system (MNS) in understanding actions and intentions is widely accepted, little is known about the time course within which these aspects of visual information are automatically extracted. Event-Related Potentials were recorded in 35 university students perceiving 260 pictures of cooperative (e.g., 2 people dragging a box) or affective (e.g., 2 people smiling and holding hands) interactions. The action's goal was automatically discriminated at about 150–170 ms, as reflected by occipito/temporal N170 response. The swLORETA inverse solution revealed the strongest sources in the right posterior cingulate cortex (CC) for affective actions and in the right pSTS for cooperative actions. It was found a right hemispheric asymmetry that involved the fusiform gyrus (BA37), the posterior CC, and the medial frontal gyrus (BA10/11) for the processing of affective interactions, particularly in the 155–175 ms time window. In a later time window (200–250 ms) the processing of cooperative interactions activated the left post-central gyrus (BA3), the left parahippocampal gyrus, the left superior frontal gyrus (BA10), as well as the right premotor cortex (BA6). Women showed a greater response discriminative of the action's goal compared to men at P300 and anterior negativity level (220–500 ms). These findings might be related to a greater responsiveness of the female vs. male MNS. In addition, the discriminative effect was bilateral in women and was smaller and left-sided in men. Evidence was provided that perceptually similar social interactions are discriminated on the basis of the agents' intentions quite early in neural processing, differentially activating regions devoted to face/body/action coding, the limbic system and the MNS

Semantic modelling of user interests based on cross-folksonomy analysis

The continued increase in Web usage, in particular participation in folksonomies, reveals a trend towards a more dynamic and interactive Web where individuals can organise and share resources. Tagging has emerged as the de-facto standard for the organisation of such resources, providing a versatile and reactive knowledge management mechanism that users find easy to use and understand. It is common nowadays for users to have multiple profiles in various folksonomies, thus distributing their tagging activities. In this paper, we present a method for the automatic consolidation of user profiles across two popular social networking sites, and subsequent semantic modelling of their interests utilising Wikipedia as a multi-domain model. We evaluate how much can be learned from such sites, and in which domains the knowledge acquired is focussed. Results show that far richer interest profiles can be generated for users when multiple tag-clouds are combine