Simple Coalitional Games with Beliefs

We introduce coalitional games with beliefs (CGBs), a natural generalization of coalitional games to environments where agents possess private beliefs regarding the capabilities (or types) of others. We put forward a model to capture such agent-type uncertainty, and study coalitional stability in this setting. Specifically, we introduce a notion of the core for CGBs, both with and without coalition structures. For simple games without coalition structures, we then provide a characterization of the core that matches the one for the full information case, and use it to derive a polynomial-time algorithm to check core nonemptiness. In contrast, we demonstrate that in games with coalition structures allowing beliefs increases the computational complexity of stability-related problems. In doing so, we introduce and analyze weighted voting games with beliefs, which may be of independent interest. Finally, we discuss connections between our model and other classes of coalitional games

Sequential Decision Making in Repeated Coalition Formation under Uncertainty

The problem of coalition formation when agents are uncertain about the types or capabilities of their potential partners is a critical one. In [3] a Bayesian reinforcement learning framework is developed for this problem when coalitions are formed (and tasks undertaken) repeatedly: not only does the model allow agents to refine their beliefs about the types of others, but uses value of information to define optimal exploration policies. However, computational approximations in that work are purely myopic. We present novel, non-myopic learning algorithms to approximate the optimal Bayesian solution, providing tractable means to ensure good sequential performance. We evaluate our algorithms in a variety of settings, and show that one, in particular, exhibits consistently good sequential performance. Further, it enables the Bayesian agents to transfer acquired knowledge among different dynamic tasks

Cooperatives for demand side management

We propose a new scheme for efficient demand side management for the Smart Grid. Specifically, we envisage and promote the formation of cooperatives of medium-large consumers and equip them (via our proposed mechanisms) with the capability of regularly participating in the existing electricity markets by providing electricity demand reduction services to the Grid. Based on mechanism design principles, we develop a model for such cooperatives by designing methods for estimating suitable reduction amounts, placing bids in the market and redistributing the obtained revenue amongst the member agents. Our mechanism is such that the member agents have no incentive to show artificial reductions with the aim of increasing their revenue

Influence of State-Variable Constraints on Partially Observable Monte Carlo Planning

Online planning methods for partially observable Markov decision processes (POMDPs) have re- cently gained much interest. In this paper, we pro- pose the introduction of prior knowledge in the form of (probabilistic) relationships among dis- crete state-variables, for online planning based on the well-known POMCP algorithm. In particu- lar, we propose the use of hard constraint net- works and probabilistic Markov random fields to formalize state-variable constraints and we extend the POMCP algorithm to take advantage of these constraints. Results on a case study based on Rock- sample show that the usage of this knowledge pro- vides significant improvements to the performance of the algorithm. The extent of this improvement depends on the amount of knowledge encoded in the constraints and reaches the 50% of the average discounted return in the most favorable cases that we analyzed

Cooperative Games with Overlapping Coalitions

In the usual models of cooperative game theory, the outcome of a coalition formation process is either the grand coalition or a coalition structure that consists of disjoint coalitions. However, in many domains where coalitions are associated with tasks, an agent may be involved in executing more than one task, and thus may distribute his resources among several coalitions. To tackle such scenarios, we introduce a model for cooperative games with overlapping coalitions--or overlapping coalition formation (OCF) games. We then explore the issue of stability in this setting. In particular, we introduce a notion of the core, which generalizes the corresponding notion in the traditional (non-overlapping) scenario. Then, under some quite general conditions, we characterize the elements of the core, and show that any element of the core maximizes the social welfare. We also introduce a concept of balancedness for overlapping coalitional games, and use it to characterize coalition structures that can be extended to elements of the core. Finally, we generalize the notion of convexity to our setting, and show that under some natural assumptions convex games have a non-empty core. Moreover, we introduce two alternative notions of stability in OCF that allow a wider range of deviations, and explore the relationships among the corresponding definitions of the core, as well as the classic (non-overlapping) core and the Aubin core. We illustrate the general properties of the three cores, and also study them from a computational perspective, thus obtaining additional insights into their fundamental structure

Bayesian Active Malware Analysis

We propose a novel technique for Active Malware Analysis (AMA) formalized as a Bayesian game between an analyzer agent and a malware agent, focusing on the decision making strategy for the analyzer. In our model, the analyzer performs an action on the system to trigger the malware into showing a malicious behavior, i.e., by activating its payload. The formalization is built upon the link between malware families and the notion of types in Bayesian games. A key point is the design of the utility function, which reflects the amount of uncertainty on the type of the adversary after the execution of an analyzer action. This allows us to devise an algorithm to play the game with the aim of minimizing the entropy of the analyzer's belief at every stage of the game in a myopic fashion. Empirical evaluation indicates that our approach results in a significant improvement both in terms of learning speed and classification score when compared to other state-of-the-art AMA techniques

Η δημιουργία κουρδικού κράτους ως γεωπολιτικός παράγων ανακατανομής ισχύος στο γεωπολιτικό σύμπλοκο της Ευρύτερης Μέσης Ανατολής.

Το παρόν πόνημα αποτελεί μεταπτυχιακή διπλωματική εργασία με τίτλο: «Η δημιουργία κουρδικού κράτους ως γεωπολιτικός παράγων ανακατανομής ισχύος στο γεωπολιτικό σύμπλοκο της Ευρύτερης Μέσης Ανατολής». Συνοπτικά, πρόκειται για την επιστημονική προσέγγιση του ζητήματος διαμέσων της εφαρμογής της συστημικής γεωπολιτικής ανάλυσης, στο γεωπολιτικό σύμπλοκο της Μέσης Ανατολής. Θα αναπτυχθούν οι γεωπολιτικοί προβληματισμοί που προκύπτουν, και σαφώς, θα εξετασθεί η ανακατανομή της ισχύος που θα επέλθει στην ευρύτερη περιοχή της Μέσης Ανατολής, αναλύοντας τον Πολιτισμικό, Οικονομικό και Πολιτικό πυλώνα ισχύος.This is a postgraduate thesis entitled: "The creation of a Kurdish state as a geopolitical factor of power redistribution in the geopolitical complex of the Wider Middle East." In short, this is the scientific approach to the issue through the application of systemic geopolitical analysis to the geopolitical complex of the Middle East. The resulting geopolitical concerns will be developed regarding the redistribution of power that will occur in the wider Middle East, by analyzing the Cultural, Economic and Political pillar of power