A resource based game theoretical model for military conflicts

A resource interaction based game theoretical model for military conflicts is presented in this paper. The model includes both the spatial decision capability of adversaries (decision regarding movement and subsequent distribution of resources) as well as their temporal decision capability (decision regarding level of allocation of resources for conflict with adversary’s resources). Attrition is decided at present by simple deterministic models. An additional feature of this model is the inclusion of the possibility of a given resource interacting with several resources of the adversary.The decisions of the adversaries is determined by solving for the equilibrium Nash strategies given that the objectives of the adversaries may not be in direct conflict. Examples are given to show the applicability of these models and solution concepts.

A game theoretic approach for feature clustering and its application to feature selection

In this paper, we develop a game theoretic approach for clustering features in a learning problem. Feature clustering can serve as an important preprocessing step in many problems such as feature selection, dimensionality reduction, etc. In this approach, we view features as rational players of a coalitional game where they form coalitions (or clusters) among themselves in order to maximize their individual payoffs. We show how Nash Stable Partition (NSP), a well known concept in the coalitional game theory, provides a natural way of clustering features. Through this approach, one can obtain some desirable properties of the clusters by choosing appropriate payoff functions. For a small number of features, the NSP based clustering can be found by solving an integer linear program (ILP). However, for large number of features, the ILP based approach does not scale well and hence we propose a hierarchical approach. Interestingly, a key result that we prove on the equivalence between a k-size NSP of a coalitional game and minimum k-cut of an appropriately constructed graph comes in handy for large scale problems. In this paper, we use feature selection problem (in a classification setting) as a running example to illustrate our approach. We conduct experiments to illustrate the efficacy of our approach.

Pattern clustering using cooperative game theory

In this paper, we approach the classical problem of clustering using solution concepts from cooperative game theory such as Nucleolus and Shapley value. We formulate the problem of clustering as a characteristic form game and develop a novel algorithm DRAC (Density-Restricted Agglomerative Clustering) for clustering. With extensive experimentation on standard data sets, we compare the performance of DRAC with that of well known algorithms. We show an interesting result that four prominent solution concepts, Nucleolus, Shapley value, Gately point and \tau-value coincide for the defined characteristic form game. This vindicates the choice of the characteristic function of the clustering game and also provides strong intuitive foundation for our approach.

Game theoretic, decentralized, local information based algorithm for community detection in social graphs

Motivated by the observation that communities in real world social networks form due to actions of rational individuals in networks, we propose a novel game theory inspired algorithm to determine communities in networks. The algorithm is decentralized and only uses local information at each node. We show the efficacy of the proposed algorithm through extensive experimentation on several real world social network data sets.

Sustaining cooperation on networks: an analytical study based on evolutionary game theory

We analytically study the role played by the network topology in sustaining cooperation in a society of myopic agents in an evolutionary setting. In our model, each agent plays the Prisoner's Dilemma (PD) game with its neighbors, as specified by a network. Cooperation is the incumbent strategy, whereas defectors are the mutants. Starting with a population of cooperators, some agents are switched to defection. The agents then play the PD game with their neighbors and compute their fitness. After this, an evolutionary rule, or imitation dynamic is used to update the agent strategy. A defector switches back to cooperation if it has a cooperator neighbor with higher fitness. The network is said to sustain cooperation if almost all defectors switch to cooperation. Earlier work on the sustenance of cooperation has largely consisted of simulation studies, and we seek to complement this body of work by providing analytical insight for the same. We find that in order to sustain cooperation, a network should satisfy some properties such as small average diameter, densification, and irregularity. Real-world networks have been empirically shown to exhibit these properties, and are thus candidates for the sustenance of cooperation. We also analyze some specific graphs to determine whether or not they sustain cooperation. In particular, we find that scale-free graphs belonging to a certain family sustain cooperation, whereas Erdos-Renyi random graphs do not. To the best of our knowledge, ours is the first analytical attempt to determine which networks sustain cooperation in a population of myopic agents in an evolutionary setting.

Game theoretic analysis of collusions in nonneutral networks

This paper studies the impact of exclusive contracts between a content provider (CP) and an internet service provider (ISP) in a nonneutral network. We consider a simple linear demand function for the CPs. We studywhen an exclusive contract is benefcial to the colluding pair and evaluate its impact on the noncolluding players at equilibrium. For the case of two CPs and one ISP we show that collusion may not always be benefcial. We derive an explicit condition in terms of the advertisement revenues of the CPs that tells when a collusion is proftable to the colluding entities.

Novel Biobjective Clustering (BiGC) Based on Cooperative Game Theory

We propose a new approach to clustering. Our idea is to map cluster formation to coalition formation in cooperative games, and to use the Shapley value of the patterns to identify clusters and cluster representatives. We show that the underlying game is convex and this leads to an efficient biobjective clustering algorithm that we call BiGC. The algorithm yields high-quality clustering with respect to average point-to-center distance (potential) as well as average intracluster point-to-point distance (scatter). We demonstrate the superiority of BiGC over state-of-the-art clustering algorithms (including the center based and the multiobjective techniques) through a detailed experimentation using standard cluster validity criteria on several benchmark data sets. We also show that BiGC satisfies key clustering properties such as order independence, scale invariance, and richness.

Two player game variant of the Erdos-Szekeres problem

The classical Erdos-Szekeres theorem states that a convex k-gon exists in every sufficiently large point set. This problem has been well studied and finding tight asymptotic bounds is considered a challenging open problem. Several variants of the Erdos-Szekeres problem have been posed and studied in the last two decades. The well studied variants include the empty convex k-gon problem, convex k-gon with specified number of interior points and the chromatic variant. In this paper, we introduce the following two player game variant of the Erdos-Szekeres problem: Consider a two player game where each player playing in alternate turns, place points in the plane. The objective of the game is to avoid the formation of the convex k-gon among the placed points. The game ends when a convex k-gon is formed and the player who placed the last point loses the game. In our paper we show a winning strategy for the player who plays second in the convex 5-gon game and the empty convex 5-gon game by considering convex layer configurations at each step. We prove that the game always ends in the 9th step by showing that the game reaches a specific set of configurations.

Pricing and Power allocation in Femtocells using Stackelberg Game Theory

We consider a system with multiple Femtocells operating in a Macrocell. The transmissions in one Femtocell interfere with its neighboring Femtocells as well as with the Macrocell Base Station. We model Femtocells as selfish nodes and the Macrocell Base Station protects itself by pricing subchannels for each usage. We use Stackelberg game model to study this scenario and obtain equilibrium policies that satisfy certain quality of service.

Object attributes combine additively in visual search

We perceive objects as containing a variety of attributes: local features, relations between features, internal details, and global properties. But we know little about how they combine. Here, we report a remarkably simple additive rule that governs how these diverse object attributes combine in vision. The perceived dissimilarity between two objects was accurately explained as a sum of (a) spatially tuned local contour-matching processes modulated by part decomposition; (b) differences in internal details, such as texture; (c) differences in emergent attributes, such as symmetry; and (d) differences in global properties, such as orientation or overall configuration of parts. Our results elucidate an enduring question in object vision by showing that the whole object is not a sum of its parts but a sum of its many attributes.

Neighborhoods attributes as determinants of children's academic achievement

Resumen: Los estudios sobre los efectos del vecindario sobre los logros educativos han confirmado la existencia de estos efectos particularmente en la adolescencia. Una deficiencia común de la investigación empírica hasta la fecha, la falta de información en múltiples contextos, se aborda en este trabajo mediante el uso de encuestas escolares de datos para obtener una mayor comprensión sobre el efecto de la pobreza en los niños que cursan el nivel primario de enseñanza en los EE.UU. Este trabajo propone la utilización de un modelo jerárquico lineal de clasificación cruzada para tomar en cuenta en forma apropiada la estructura anidada de la información ya que los niños pertenecen simultáneamente a los dos grupos, el barrio y la escuela. Los resultados que se presentan, basados en la encuesta ECLS-K, una muestra de más de 20000 niños en aproximadamente 1.000 vecindarios y 1200 escuelas 1200, pone de manifiesto la asociación entre la composición socioeconómica del vecindario y los resultados académicos de los estudiantes. Este estudio proporciona evidencia a favor de las teorías de la socialización y epidémica. La presencia de adultos con buen nivel educativo en el vecindario así como la mediana de ingresos tienen impacto positivo en el logro del estudiante. De la misma forma, elevados niveles de pobreza tienen una influencia significativa, pero negativa en los resultados académicos. Sin embargo, el impacto se produce cuando se supera el umbral de 30% de hogares pobres en el vecindario. Los resultados agregados son invariantes a distintas especificaciones en términos de variables, esto no sucede cuando se analizan subgrupos clasificados según su origen étnico, género y estatus socio-económico.

Implementing with veto players: a simple non cooperative game

The paper adapts a non cooperative game presented by Dagan, Serrano and Volij (1997) for bankruptcy problems to the context of TU veto balanced games. We investigate the relationship between the Nash outcomes of a noncooperative game and solution concepts of cooperative games such as the nucleolus, kernel and the egalitarian core.

Competitive Pressure and Job Interview Lying: A Game Theoretical Analysis

We consider a job contest in which candidates go through interviews (cheap talk) and are subject to reference checks. We show how competitive pressure - increasing the ratio of "good" to "bad" type candi- dates - can lead to a vast increase in lying and in some cases make bad hires more likely. As the number of candidates increases, it becomes harder to in- duce truth-telling. The interview stage becomes redundant if the candidates, a priori, know each others' type or the result of their own reference check. Finally, we show that the employer can bene t from committing not to reject all the applicants.