Interactive Epistemology and Reasoning: On the Foundations of Game Theory

Game theory describes and analyzes strategic interaction. It is usually distinguished between static games, which are strategic situations in which the players choose only once as well as simultaneously, and dynamic games, which are strategic situations involving sequential choices. In addition, dynamic games can be further classified according to perfect and imperfect information. Indeed, a dynamic game is said to exhibit perfect information, whenever at any point of the game every player has full informational access to all choices that have been conducted so far. However, in the case of imperfect information some players are not fully informed about some choices. Game-theoretic analysis proceeds in two steps. Firstly, games are modelled by so-called form structures which extract and formalize the significant parts of the underlying strategic interaction. The basic and most commonly used models of games are the normal form, which rather sparsely describes a game merely in terms of the players' strategy sets and utilities, and the extensive form, which models a game in a more detailed way as a tree. In fact, it is standard to formalize static games with the normal form and dynamic games with the extensive form. Secondly, solution concepts are developed to solve models of games in the sense of identifying the choices that should be taken by rational players. Indeed, the ultimate objective of the classical approach to game theory, which is of normative character, is the development of a solution concept that is capable of identifying a unique choice for every player in an arbitrary game. However, given the large variety of games, it is not at all certain whether it is possible to device a solution concept with such universal capability. Alternatively, interactive epistemology provides an epistemic approach to game theory of descriptive character. This rather recent discipline analyzes the relation between knowledge, belief and choice of game-playing agents in an epistemic framework. The description of the players' choices in a given game relative to various epistemic assumptions constitutes the fundamental problem addressed by an epistemic approach to game theory. In a general sense, the objective of interactive epistemology consists in characterizing existing game-theoretic solution concepts in terms of epistemic assumptions as well as in proposing novel solution concepts by studying the game-theoretic implications of refined or new epistemic hypotheses. Intuitively, an epistemic model of a game can be interpreted as representing the reasoning of the players. Indeed, before making a decision in a game, the players reason about the game and their respective opponents, given their knowledge and beliefs. Precisely these epistemic mental states on which players base their decisions are explicitly expressible in an epistemic framework. In this PhD thesis, we consider an epistemic approach to game theory from a foundational point of view. In Chapter 1, basic game-theoretic notions as well as Aumann's epistemic framework for games are expounded and illustrated. Also, Aumann's sufficient conditions for backward induction are presented and his conceptual views discussed. In Chapter 2, Aumann's interactive epistemology is conceptually analyzed. In Chapter 3, which is based on joint work with Conrad Heilmann, a three-stage account for dynamic games is introduced and a type-based epistemic model is extended with a notion of agent connectedness. Then, sufficient conditions for backward induction are derived. In Chapter 4, which is based on joint work with Jérémie Cabessa, a topological approach to interactive epistemology is initiated. In particular, the epistemic-topological operator limit knowledge is defined and some implications for games considered. In Chapter 5, which is based on joint work with Jérémie Cabessa and Andrés Perea, Aumann's impossibility theorem on agreeing to disagree is revisited and weakened in the sense that possible contexts are provided in which agents can indeed agree to disagree.

Stochastic game theory: For playing games, not just for doing theory

Recent theoretical advances have dramatically increased the relevance of game theory for predicting human behavior in interactive situations. By relaxing the classical assumptions of perfect rationality and perfect foresight, we obtain much improved explanations of initial decisions, dynamic patterns of learning and adjustment, and equilibrium steady-state distributions.

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.

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.

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.

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.

Coalition of distributed generation units to Virtual Power Players - a game theory approach

Smart Grids (SGs) have emerged as the new paradigm for power system operation and management, being designed to include large amounts of distributed energy resources. This new paradigm requires new Energy Resource Management (ERM) methodologies considering different operation strategies and the existence of new management players such as several types of aggregators. This paper proposes a methodology to facilitate the coalition between distributed generation units originating Virtual Power Players (VPP) considering a game theory approach. The proposed approach consists in the analysis of the classifications that were attributed by each VPP to the distributed generation units, as well as in the analysis of the previous established contracts by each player. The proposed classification model is based in fourteen parameters including technical, economical and behavioural ones. Depending of the VPP strategies, size and goals, each parameter has different importance. VPP can also manage other type of energy resources, like storage units, electric vehicles, demand response programs or even parts of the MV and LV distribution network. A case study with twelve VPPs with different characteristics and one hundred and fifty real distributed generation units is included in the paper.

Decision Support for Energy Contracts Negotiation with Game Theory and Adaptive Learning

This paper presents a decision support methodology for electricity market players’ bilateral contract negotiations. The proposed model is based on the application of game theory, using artificial intelligence to enhance decision support method’s adaptive features. This model is integrated in AiD-EM (Adaptive Decision Support for Electricity Markets Negotiations), a multi-agent system that provides electricity market players with strategic behavior capabilities to improve their outcomes from energy contracts’ negotiations. Although a diversity of tools that enable the study and simulation of electricity markets has emerged during the past few years, these are mostly directed to the analysis of market models and power systems’ technical constraints, making them suitable tools to support decisions of market operators and regulators. However, the equally important support of market negotiating players’ decisions is being highly neglected. The proposed model contributes to overcome the existing gap concerning effective and realistic decision support for electricity market negotiating entities. The proposed method is validated by realistic electricity market simulations using real data from the Iberian market operator—MIBEL. Results show that the proposed adaptive decision support features enable electricity market players to improve their outcomes from bilateral contracts’ negotiations.

Three essays on game theory and bargaining

A PhD Dissertation, presented as part of the requirements for the Degree of Doctor of Philosophy from the NOVA - School of Business and Economics

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.