Transmission cost allocation using cooperative game theory: a comparative study

In this paper is presented a Game Theory based methodology to allocate transmission costs, considering cooperation and competition between producers. As original contribution, it finds the degree of participation on the additional costs according to the demand behavior. A comparative study was carried out between the obtained results using Nucleolus balance and Shapley Value, with other techniques such as Averages Allocation method and the Generalized Generation Distribution Factors method (GGDF). As example, a six nodes network was used for the simulations. The results demonstrate the ability to find adequate solutions on open access environment to the networks.

Reactive Control for Transmission Overload Relief Based on Sensitivity Analysis and Cooperative Game Theory

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A cooperative game theory analysis for transmission loss allocation

This paper presents an analysis and discussion, based on cooperative game theory, for the allocation of the cost of losses to generators and demands in transmission systems. We construct a cooperative game theory model in which the players are represented by equivalent bilateral exchanges and we search for a unique loss allocation solution, the Core. Other solution concepts, such as the Shapley Value, the Bilateral Shapley Value and the Kernel are also explored. Our main objective is to illustrate why is not possible to find an optimal solution for allocating the cost of losses to the users of a network. Results and relevant conclusions are presented for a 4-bus system and a 14-bus system. (c) 2007 Elsevier B.V. All rights reserved.

Cooperation in an HMMS-type supply chain: A management application of cooperative game theory = Kooperáció egy HMMS-típusú ellátási láncban: A kooperatív játékelmélet egy menedzsment alkalmazása

We apply cooperative game theory concepts to analyze a Holt-Modigliani-Muth-Simon (HMMS) supply chain. The bullwhip effect in a two-stage supply chain (supplier-manufacturer) in the framework of the HMMS-model with quadratic cost functions is considered. It is assumed that both firms minimize their relevant costs, and two cases are examined: the supplier and the manufacturer minimize their relevant costs in a decentralized and in a centralized (cooperative) way. The question of how to share the savings of the decreased bullwhip effect in the centralized (cooperative) model is answered by the weighted Shapley value, by a transferable utility cooperative game theory tool, where the weights are for the exogenously given “bargaining powers” of the participants of the supply chain. = A cikkben a kooperatív játékelmélet fogalmait alkalmazzuk egy Holt-Mogigliani-Muth-Simon-típusú ellátási lánc esetében. Az ostorcsapás-hatás elemeit egy beszállító-termelő ellátási láncban ragadjuk meg egy kvadratikus készletezési és termelési költség mellett. Feltételezzük, hogy mindkét vállalat minimalizálja a releváns költségeit. Két működési rendszert hasonlítunk össze: egy hierarchikus döntéshozatali rendszert, amikor először a termelő, majd a beszállító optimalizálja helyzetét, majd egy centralizált (kooperatív) modellt, amikor a vállalatok az együttes költségüket minimalizálják. A kérdés úgy merül fel, hogy a csökkentett ostorcsapás-hatás esetén hogyan osszák meg a részvevők ebben a transzferálható hasznosságú kooperatív játékban a költség megtakarítást, exogén módon adott tárgyalási pozíció mellett.

Cooperation in supply chains: A cooperative game theoretic analysis = Együttműködés ellátási láncokban: Egy kooperatív játékelméleti elemzés

A cikkben a kooperatív játékelmélet fogalmait alkalmazzuk egy ellátási lánc esetében. Az ostorcsapás-hatás elemeit egy beszállító-termelő ellátási láncban ragadjuk meg egy Arrow-Karlin típusú modellben lineáris készletezési és konvex termelési költség mellett. Feltételezzük, hogy mindkét vállalat minimalizálja a fontosabb költségeit. Két működési rendszert hasonlítunk össze: egy hierarchikus döntéshozatali rendszert, amikor először a termelő, majd a beszállító optimalizálja helyzetét, majd egy centralizált (kooperatív) modellt, amikor a vállalatok az együttes költségüket minimalizálják. A kérdés úgy merül fel, hogy a csökkentett ostorcsapás-hatás esetén hogyan osszák meg a részvevők ebben a transzferálható hasznosságú kooperatív játékban. = In this paper we apply cooperative game theory concepts to analyze supply chains. The bullwhip effect in a two-stage supply chain (supplier-manufacturer) in the framework of the Arrow-Karlin model with linear-convex cost functions is considered. It is assumed that both firms minimize their relevant costs, and two cases are examined: the supplier and the manufacturer minimize their relevant costs in a decentralized and in a centralized (cooperative) way. The question of how to share the savings of the decreased bullwhip effect in the centralized (cooperative) model is answered by transferable utility cooperative game theory tools.

Cooperative Multi-robot Patrolling: A study of distributed approaches based on mathematical models of game theory to protect infrastructures

El principio de Teoría de Juegos permite desarrollar modelos estocásticos de patrullaje multi-robot para proteger infraestructuras criticas. La protección de infraestructuras criticas representa un gran reto para los países al rededor del mundo, principalmente después de los ataques terroristas llevados a cabo la década pasada. En este documento el termino infraestructura hace referencia a aeropuertos, plantas nucleares u otros instalaciones. El problema de patrullaje se define como la actividad de patrullar un entorno determinado para monitorear cualquier actividad o sensar algunas variables ambientales. En esta actividad, un grupo de robots debe visitar un conjunto de puntos de interés definidos en un entorno en intervalos de tiempo irregulares con propósitos de seguridad. Los modelos de partullaje multi-robot son utilizados para resolver este problema. Hasta el momento existen trabajos que resuelven este problema utilizando diversos principios matemáticos. Los modelos de patrullaje multi-robot desarrollados en esos trabajos representan un gran avance en este campo de investigación. Sin embargo, los modelos con los mejores resultados no son viables para aplicaciones de seguridad debido a su naturaleza centralizada y determinista. Esta tesis presenta cinco modelos de patrullaje multi-robot distribuidos e impredecibles basados en modelos matemáticos de aprendizaje de Teoría de Juegos. El objetivo del desarrollo de estos modelos está en resolver los inconvenientes presentes en trabajos preliminares. Con esta finalidad, el problema de patrullaje multi-robot se formuló utilizando conceptos de Teoría de Grafos, en la cual se definieron varios juegos en cada vértice de un grafo. Los modelos de patrullaje multi-robot desarrollados en este trabajo de investigación se han validado y comparado con los mejores modelos disponibles en la literatura. Para llevar a cabo tanto la validación como la comparación se ha utilizado un simulador de patrullaje y un grupo de robots reales. Los resultados experimentales muestran que los modelos de patrullaje desarrollados en este trabajo de investigación trabajan mejor que modelos de trabajos previos en el 80% de 150 casos de estudio. Además de esto, estos modelos cuentan con varias características importantes tales como distribución, robustez, escalabilidad y dinamismo. Los avances logrados con este trabajo de investigación dan evidencia del potencial de Teoría de Juegos para desarrollar modelos de patrullaje útiles para proteger infraestructuras. ABSTRACT Game theory principle allows to developing stochastic multi-robot patrolling models to protect critical infrastructures. Critical infrastructures protection is a great concern for countries around the world, mainly due to terrorist attacks in the last decade. In this document, the term infrastructures includes airports, nuclear power plants, and many other facilities. The patrolling problem is defined as the activity of traversing a given environment to monitoring any activity or sensing some environmental variables If this activity were performed by a fleet of robots, they would have to visit some places of interest of an environment at irregular intervals of time for security purposes. This problem is solved using multi-robot patrolling models. To date, literature works have been solved this problem applying various mathematical principles.The multi-robot patrolling models developed in those works represent great advances in this field. However, the models that obtain the best results are unfeasible for security applications due to their centralized and predictable nature. This thesis presents five distributed and unpredictable multi-robot patrolling models based on mathematical learning models derived from Game Theory. These multi-robot patrolling models aim at overcoming the disadvantages of previous work. To this end, the multi-robot patrolling problem was formulated using concepts of Graph Theory to represent the environment. Several normal-form games were defined at each vertex of a graph in this formulation. The multi-robot patrolling models developed in this research work have been validated and compared with best ranked multi-robot patrolling models in the literature. Both validation and comparison were preformed by using both a patrolling simulator and real robots. Experimental results show that the multirobot patrolling models developed in this research work improve previous ones in as many as 80% of 150 cases of study. Moreover, these multi-robot patrolling models rely on several features to highlight in security applications such as distribution, robustness, scalability, and dynamism. The achievements obtained in this research work validate the potential of Game Theory to develop patrolling models to protect infrastructures.

Spiteful Strategies. The ontogeny and the practice of spite in human interaction: an experimental game theory approach and empirical applications

As estratégias de malevolência implicam que um indivíduo pague um custo para infligir um custo superior a um oponente. Como um dos comportamentos fundamentais da sociobiologia, a malevolência tem recebido menos atenção que os seus pares o egoísmo e a cooperação. Contudo, foi estabelecido que a malevolência é uma estratégia viável em populações pequenas quando usada contra indivíduos negativamente geneticamente relacionados pois este comportamento pode i) ser eliminado naturalmente, ou ii) manter-se em equilíbrio com estratégias cooperativas devido à disponibilidade da parte de indivíduos malevolentes de pagar um custo para punir. Esta tese propõe compreender se a propensão para a malevolência nos humanos é inerente ou se esta se desenvolve com a idade. Para esse efeito, considerei duas experiências de teoria de jogos em crianças em ambiente escolar com idades entre os 6 e os 22 anos. A primeira, um jogo 2x2 foi testada com duas variantes: 1) um prémio foi atribuído a ambos os jogadores, proporcionalmente aos pontos acumulados; 2), um prémio foi atribuído ao jogador com mais pontos. O jogo foi desenhado com o intuito de causar o seguinte dilema a cada jogador: i) maximizar o seu ganho e arriscar ter menos pontos que o adversário; ou ii) decidir não maximizar o seu ganho, garantindo que este não era inferior ao do seu adversário. A segunda experiência consistia num jogo do ditador com duas opções: uma escolha egoísta/altruísta (A), onde o ditador recebia mais ganho, mas o seu recipiente recebia mais que ele e uma escolha malevolente (B) que oferecia menos ganhos ao ditador que a A mas mais ganhos que o recipiente. O dilema era que se as crianças se comportassem de maneira egoísta, obtinham mais ganho para si, ao mesmo tempo que aumentavam o ganho do seu colega. Se fossem malevolentes, então prefeririam ter mais ganho que o seu colega ao mesmo tempo que tinham menos para eles próprios. As experiências foram efetuadas em escolas de duas áreas distintas de Portugal (continente e Açores) para perceber se as preferências malevolentes aumentavam ou diminuíam com a idade. Os resultados na primeira experiência sugerem que (1) os alunos compreenderam a primeira variante como um jogo de coordenação e comportaram-se como maximizadores, copiando as jogadas anteriores dos seus adversários; (2) que os alunos repetentes se comportaram preferencialmente como malevolentes, mais frequentemente que como maximizadores, com especial ênfase para os alunos de 14 anos; (3) maioria dos alunos comportou-se reciprocamente desde os 12 até aos 16 anos de idade, após os quais começaram a desenvolver uma maior tolerância às escolhas dos seus parceiros. Os resultados da segunda experiência sugerem que (1) as estratégias egoístas eram prevalentes até aos 6 anos de idade, (2) as tendências altruístas emergiram até aos 8 anos de idade e (3) as estratégias de malevolência começaram a emergir a partir dos 8 anos de idade. Estes resultados complementam a literatura relativamente escassa sobre malevolência e sugerem que este comportamento está intimamente ligado a preferências de consideração sobre os outros, o paroquialismo e os estágios de desenvolvimento das crianças.************************************************************Spite is defined as an act that causes loss of payoff to an opponent at a cost to the actor. As one of the four fundamental behaviours in sociobiology, it has received far less attention than its counterparts selfishness and cooperation. It has however been established as a viable strategy in small populations when used against negatively related individuals. Because of this, spite can either i) disappear or ii) remain at equilibrium with cooperative strategies due to the willingness of spiteful individuals to pay a cost in order to punish. This thesis sets out to understand whether propensity for spiteful behaviour is inherent or if it develops with age. For that effect, two game-theoretical experiments were performed with schoolboys and schoolgirls aged 6 to 22. The first, a 2 x 2 game, was tested in two variants: 1) a prize was awarded to both players, proportional to accumulated points; 2), a prize was given to the player with most points. Each player faced the following dilemma: i) to maximise pay-off risking a lower pay-off than the opponent; or ii) not to maximise pay-off in order to cut down the opponent below their own. The second game was a dictator experiment with two choices, (A) a selfish/altruistic choice affording more payoff to the donor than B, but more to the recipient than to the donor, and (B) a spiteful choice that afforded less payoff to the donor than A, but even lower payoff to the recipient. The dilemma here was that if subjects behaved selfishly, they obtained more payoff for themselves, while at the same time increasing their opponent payoff. If they were spiteful, they would rather have more payoff than their colleague, at the cost of less for themselves. Experiments were run in schools in two different areas in Portugal (mainland and Azores) to understand whether spiteful preferences varied with age. Results in the first experiment suggested that (1) students understood the first variant as a coordination game and engaged in maximising behaviour by copying their opponent’s plays; (2) repeating students preferentially engaged in spiteful behaviour more often than maximising behaviour, with special emphasis on 14 year-olds; (3) most students engaged in reciprocal behaviour from ages 12 to 16, as they began developing higher tolerance for their opponent choices. Results for the second experiment suggested that (1) selfish strategies were prevalent until the age of 6, (2) altruistic tendencies emerged since then, and (3) spiteful strategies began being chosen more often by 8 year-olds. These results add to the relatively scarce body of literature on spite and suggest that this type of behaviour is closely tied with other-regarding preferences, parochialism and the children’s stages of development.

Game theory and reciprocity in some extensive form experimental games

We examine decision making in two-person extensive form game trees using nine treatments that vary matching protocol, payoffs, and payoff information. Our objective is to establish replicable principles of cooperative versus noncooperative behavior that involve the use of signaling, reciprocity, and backward induction strategies, depending on the availability of dominated direct punishing strategies and the probability of repeated interaction with the same partner. Contrary to the predictions of game theory, we find substantial support for cooperation under complete information even in various single-play treatments.

Experimental results on the nonlinear H(infinity) control via quasi-LPV representation and game theory for wheeled mobile robots

In this paper, nonlinear dynamic equations of a wheeled mobile robot are described in the state-space form where the parameters are part of the state (angular velocities of the wheels). This representation, known as quasi-linear parameter varying, is useful for control designs based on nonlinear H(infinity) approaches. Two nonlinear H(infinity) controllers that guarantee induced L(2)-norm, between input (disturbances) and output signals, bounded by an attenuation level gamma, are used to control a wheeled mobile robot. These controllers are solved via linear matrix inequalities and algebraic Riccati equation. Experimental results are presented, with a comparative study among these robust control strategies and the standard computed torque, plus proportional-derivative, controller.

Role of price and enforcement in water allocation: Insights from Game Theory

As many countries are moving toward water sector reforms, practical issues of how water management institutions can better effect allocation, regulation, and enforcement of water rights have emerged. The problem of nonavailability of water to tailenders on an irrigation system in developing countries, due to unlicensed upstream diversions is well documented. The reliability of access or equivalently the uncertainty associated with water availability at their diversion point becomes a parameter that is likely to influence the application by users for water licenses, as well as their willingness to pay for licensed use. The ability of a water agency to reduce this uncertainty through effective water rights enforcement is related to the fiscal ability of the agency to monitor and enforce licensed use. In this paper, this interplay across the users and the agency is explored, considering the hydraulic structure or sequence of water use and parameters that define the users and the agency`s economics. The potential for free rider behavior by the users, as well as their proposals for licensed use are derived conditional on this setting. The analyses presented are developed in the framework of the theory of ""Law and Economics,`` with user interactions modeled as a game theoretic enterprise. The state of Ceara, Brazil, is used loosely as an example setting, with parameter values for the experiments indexed to be approximately those relevant for current decisions. The potential for using the ideas in participatory decision making is discussed. This paper is an initial attempt to develop a conceptual framework for analyzing such situations but with a focus on the reservoir-canal system water rights enforcement.

Strategic bidding in electricity markets: an agent-based simulator with game theory for scenario analysis

Electricity markets are complex environments, involving a large number of different entities, with specific characteristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to support decisions in competitive environments; therefore its application in electricity markets can prove to be a high potential tool. This paper proposes a new scenario analysis algorithm, which includes the application of game-theory, to evaluate and preview different scenarios and provide players with the ability to strategically react in order to exhibit the behavior that better fits their objectives. This model includes forecasts of competitor players’ actions, to build models of their behavior, in order to define the most probable expected scenarios. Once the scenarios are defined, game theory is applied to support the choice of the action to be performed. Our use of game theory is intended for supporting one specific agent and not for achieving the equilibrium in the market. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. The scenario analysis algorithm has been tested within MASCEM and our experimental findings with a case study based on real data from the Iberian Electricity Market are presented and discussed.

On lattices from combinatorial game theory modularity and a representation theorem: finite case

We show that a self-generated set of combinatorial games, S. may not be hereditarily closed but, strong self-generation and hereditary closure are equivalent in the universe of short games. In [13], the question "Is there a set which will give a non-distributive but modular lattice?" appears. A useful necessary condition for the existence of a finite non-distributive modular L(S) is proved. We show the existence of S such that L(S) is modular and not distributive, exhibiting the first known example. More, we prove a Representation Theorem with Games that allows the generation of all finite lattices in game context. Finally, a computational tool for drawing lattices of games is presented. (C) 2014 Elsevier B.V. All rights reserved.