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Defence date: 23 March 2015 ; Examining Board: Professor Fernando Vega-Redondo, Supervisor, Bocconi University; Professor Piero Gottardi, EUI; Professor Paolo Pin, Università degli Studi di Siena; Professor Giovanni Ponti, Universidad de Alicante. ; My thesis covers different aspects of applied game theory. The first paper looks at a two-sided asymmetric information game where agents make a collaborative decision not knowing each others' types. In the model, an intermediary has full knowledge about the types of agents and can make a decision that brings information to some types. However, once he puts the information on the table the agents are not obliged to pay him, which undermines his incentive to participate in the first place. I find that, nevertheless, the intermediary is still welfare-improving. In my second chapter I search for the optimal prize schemes in contests with sabotage. In the presence of sabotage, a standard prize scheme where all of the prize is given to the winner is no longer optimal as it creates very high incentives for sabotage. I show that in that case, an optimal prize structure may also assume a positive reward for contestants that are behind. With a higher number of contestants sabotage becomes a public good and therefore it is a lesser concern for the designer. In that case, when sabotage is expensive, the designer can achieve the first best by giving the whole sum to the winner. When I extend the problem to the continuous case the solution crucially depends on the cost of sabotage. When sabotage is expensive, the principal wants to give all of the prize to the winner, while when it is cheap he does not want to make a contest at all, and distributes all prizes equally. In the third paper we analyze to what extent knowing game theory alters a persons' behavior. Our experiment showed a huge difference in results before and after the course. However results suggest that players behave less cooperatively not because of the knowledge of game theory per se, but due to changed expectations. We have also found that a course on game theory increases the level of reasoning.

Game theory studies the strategic interactions between and among decision makers, players, through mathematical models called games. This paper presents an overview on the evolution of the application of game theory to fisheries economics. The first applications emerged in the late 1970s, focussing upon internationally shared fish stocks. This occurred in the context of the UN Third Conference on the Law of the Sea, and the 1982 UN Convention on the Law of the Sea. During the 1980s and early 1990s the application of game theory to fisheries focused mainly on transboundary fish stocks. Thereafter, the applications to straddling fish stocks developed significantly, through the use of coalition games. This was a consequence of the mismanagement of these stocks, and the management regime brought forth in response by the 1995 UN Fish Stocks Agreement. The application of game theory to the management of national/regional fisheries is a new research frontier, as it is still much underexplored, when compared to international fisheries. This paper also summarizes the main research developments of a set of nine papers selected for this special issue on Game Theory and Fisheries. ; Peer reviewed

Climate change perceptions and perceived risk in the United States has become increasingly partisan, with increased belief in and support for climate change and regulation among democrats, but decreased belief and support among republicans. These divergences are partly attributable to increasingly partisan news outlet viewership and coverage. We inhabited a game theory model to recognize optimal climate change communication strategy through news media outlets. Actor strategies included whether to converse with pro- and/or anti-climate change new outlets, and to emphasize regulation, renewable energy, whether climate change is real, man-made, and/or causes harm to the United States Payoffs consisted of change in public opinion for each of the candidate topics actors can chose to emphasize. Solutions to games where players have a continuous choice about how much to pollute, games where players make decisions about treaty participation, and games where players make decisions about treaty ratification, are examined. The implications of linking cooperation on climate change with cooperation on other issues, such as trade, are examined. Cooperative and non-cooperative approaches to coalition formation are investigated in order to examine the behavior of coalitions cooperating on climate change. One approach to accomplish assistance is to design a game, known as an apparatus, whose equilibrium corresponds to an optimal outcome.

Timing is crucial in situations ranging from product introductions, to currency attacks, to starting a revolution. These settings share the feature that payoffs depend critically on the timing of moves of a few other key players—and these are uncertain. To capture this, we introduce the notion of clock games and experimentally test them. Each player's clock starts on receiving a signal about a payoff-relevant state variable. Since the timing of the signals is random, clocks are de-synchronized. A player must decide how long, if at all, to delay his move after receiving the signal. We show that (i) equilibrium is always characterized by strategic delay—regardless of whether moves are observable or not; (ii) delay decreases as clocks become more synchronized and increases as information becomes more concentrated; (iii) When moves are observable, players "herd" immediately after any player makes a move. We then show, in a series of experiments, that key predictions of the model are consistent with observed behavior.

This paper explicitly introduces norms in games, assuming that they shape (some) players' utility. People feel badly when they deviate from a binding norm, and the less other players deviate, the more badly they feel. Further, people anger at transgressors and get pleasure from punishing them. I then study how social norms and emotions affect competition, cooperation, and punishment in a variety of games. The model is consistent with abundant experimental evidence that alternative models of social preferences cannot explain. ; Financial support from the European Union through the ENABLE Marie Curie Research Training Network.

Game theory is a branch of mathematics aimed at the modeling and understanding of resource conflict problems. Essentially, the theory splits into two branches: noncooperative and cooperative game theory. The distinction between the two is whether or not the players in the game can make joint decisions regarding the choice of strategy. Noncooperative game theory is closely connected to minimax optimization and typically results in the study of various equilibria, most notably the Nash equilibrium. Cooperative game theory examines how strictly rational (selfish) actors can benefit from voluntary cooperation by reaching bargaining agreements. Another distinction is between static and dynamic game theory, where the latter can be viewed as a combination of game theory and optimal control. In general, the theory provides a structured approach to many important problems arising in signal processing and communications, notably resource allocation and robust transceiver optimization. Recent applications also occur in other emerging fields, such as cognitive radio, spectrum sharing, and in multihop-sensor and adhoc networks.

This paper presents a succinct review of attempts in the literature to use game theory to model decision-making scenarios relevant to defence applications. Game theory has been proven as a very effective tool in modelling the decision-making processes of intelligent agents, entities, and players. It has been used to model scenarios from diverse fields such as economics, evolutionary biology, and computer science. In defence applications, there is often a need to model and predict the actions of hostile actors, and players who try to evade or out-smart each other. Modelling how the actions of competitive players shape the decision making of each other is the forte of game theory. In past decades, there have been several studies that applied different branches of game theory to model a range of defence-related scenarios. This paper provides a structured review of such attempts, and classifies existing literature in terms of the kind of warfare modelled, the types of games used, and the players involved. After careful selection, a total of 29 directly relevant papers are discussed and classified. In terms of the warfares modelled, we recognise that most papers that apply game theory in defence settings are concerned with Command and Control Warfare, and can be further classified into papers dealing with (i) Resource Allocation Warfare (ii) Information Warfare (iii) Weapons Control Warfare, and (iv) Adversary Monitoring Warfare. We also observe that most of the reviewed papers are concerned with sensing, tracking, and large sensor networks, and the studied problems have parallels in sensor network analysis in the civilian domain. In terms of the games used, we classify the reviewed papers into papers that use non-cooperative or cooperative games, simultaneous or sequential games, discrete or continuous games, and non-zero-sum or zero-sum games. Similarly, papers are also classified into two-player, three-player or multi-player game based papers. We also explore the nature of players and the construction of payoff functions in each scenario. Finally, we also identify gaps in literature where game theory could be fruitfully applied in scenarios hitherto unexplored using game theory. The presented analysis provides a concise summary of the state-of-the-art with regards to the use of game theory in defence applications and highlights the benefits and limitations of game theory in the considered scenarios.

Summarization: Rural water management is a basic requirement for the development of the primary sector and involves the exploitation of surface/ground-water resources. Rational management requires the study of parameters that determine their exploitation mainly environmental, economic and social. These parameters reflect the influence of irrigation on the aquifer behaviour and on the level-streamflow of nearby rivers as well as on the profit from the farming activity for the farmers' welfare. The question of rural water management belongs to the socio-political problems, since the factors involved are closely related to user behaviour and state position. By applying Game Theory one seeks to simulate the behaviour of the system 'surface/ground-water resources to water-users' with a model based on a well-known game, "The Prisoner's Dilemma" for economic development of the farmers without overexploitation of the water resources. This is a game of two players that have been extensively studied in Game Theory, economy and politics because it can describe real-world cases. The present proposal aims to investigate the rural water management issue that is referred to two competitive small partnerships organised to manage their agricultural production and to achieve a better profit. For the farmers' activities water is required and ground-water is generally preferable because consists a more stable recourse than river-water which in most of the cases in Greece are of intermittent flow. If the two farmer groups cooperate and exploit the agreed water quantities they will gain equal profits and benefit from the sustainable availability of the water recourses (p). If both groups overexploitate the resource to maximize profit, then in the medium-term they will incur a loss (g), due to the water resources reduction and the increase of the pumping costs. If one overexploit the resource while the other use the necessary required, then the first will gain great benefit (P), and the second will suffer a significant loss (G). ...

This paper offers certain predictions concerning the demographic population of the cities Vilnius and Olsztyn. The authors used a method of analyzing and synthesizing data sources, and comparing the actual data with the forecast between the years 1997–2014. Each prediction was prepared in connection with its use in various areas of life, particularly for all studies involving spatial planning. The data collected on the basis of the forecasts were used by spatial planners to devise strategies for local development at the city, municipality, and provincial levels. In this sense, they created basic documents for the sustainable planning of space. The process of forecasting is a difficult and complex issue, and its accuracy determines both the choice of methods and the quality of the output. Our study sets out predictions concerning the demographic processes over the coming years in the two cities mentioned. Given that all long-range forecasts are characterized by high risk, especially taking into account the unstable political situation in Europe, the steadily deteriorating situation in the labor market and rising social discontent are of relevance, as they are causing the ongoing dynamics of the population to change, making statistical errors more likely and more serious. This has meant that organizations like Poland's Central Statistical Office, Eurostat, and the United Nations have to adjust their demographic projections at least every two years, and the methods for making demographic forecasts which are used by governmental institutions have proven to be less than satisfactory. The main purpose of the article, therefore, is to present the authors' method of making demographic projections by using elements of game theory. The results obtained in this method were compared with the results of the forecasting methods currently used by the governments of Poland and Lithuania. The developed method, based on the same input data and analogous coefficients, brings more probable results

This paper offers certain predictions concerning the demographic population of the cities Vilnius and Olsztyn. The authors used a method of analyzing and synthesizing data sources, and comparing the actual data with the forecast between the years 1997–2014. Each prediction was prepared in connection with its use in various areas of life, particularly for all studies involving spatial planning. The data collected on the basis of the forecasts were used by spatial planners to devise strategies for local development at the city, municipality, and provincial levels. In this sense, they created basic documents for the sustainable planning of space. The process of forecasting is a difficult and complex issue, and its accuracy determines both the choice of methods and the quality of the output. Our study sets out predictions concerning the demographic processes over the coming years in the two cities mentioned. Given that all long-range forecasts are characterized by high risk, especially taking into account the unstable political situation in Europe, the steadily deteriorating situation in the labor market and rising social discontent are of relevance, as they are causing the ongoing dynamics of the population to change, making statistical errors more likely and more serious. This has meant that organizations like Poland's Central Statistical Office, Eurostat, and the United Nations have to adjust their demographic projections at least every two years, and the methods for making demographic forecasts which are used by governmental institutions have proven to be less than satisfactory. The main purpose of the article, therefore, is to present the authors' method of making demographic projections by using elements of game theory. The results obtained in this method were compared with the results of the forecasting methods currently used by the governments of Poland and Lithuania. The developed method, based on the same input data and analogous coefficients, brings more probable results

This paper offers certain predictions concerning the demographic population of the cities Vilnius and Olsztyn. The authors used a method of analyzing and synthesizing data sources, and comparing the actual data with the forecast between the years 1997&ndash ; 2014. Each prediction was prepared in connection with its use in various areas of life, particularly for all studies involving spatial planning. The data collected on the basis of the forecasts were used by spatial planners to devise strategies for local development at the city, municipality, and provincial levels. In this sense, they created basic documents for the sustainable planning of space. The process of forecasting is a difficult and complex issue, and its accuracy determines both the choice of methods and the quality of the output. Our study sets out predictions concerning the demographic processes over the coming years in the two cities mentioned. Given that all long-range forecasts are characterized by high risk, especially taking into account the unstable political situation in Europe, the steadily deteriorating situation in the labor market and rising social discontent are of relevance, as they are causing the ongoing dynamics of the population to change, making statistical errors more likely and more serious. This has meant that organizations like Poland&rsquo ; s Central Statistical Office, Eurostat, and the United Nations have to adjust their demographic projections at least every two years, and the methods for making demographic forecasts which are used by governmental institutions have proven to be less than satisfactory. The main purpose of the article, therefore, is to present the authors&rsquo ; method of making demographic projections by using elements of game theory. The results obtained in this method were compared with the results of the forecasting methods currently used by the governments of Poland and Lithuania. The developed method, based on the same input data and analogous coefficients, brings more probable results.

Game theory has actually been initiated by several mathematicians but game theory began to receive widespread attention since the publication of a book entitled Theory of Games and Economic Behavior, in 1944, which was written by a mathematician John von Neumann and economists Oskar Morgenstern. Game theory continues to evolve to this day and although it is still considered as part of economics but game theory had been applied in various disciplines such as psychology, politics, management, social sciences. So that people can understand it more easily, can be used examples of simple games, among others, two-person zero-sum game, maximin and minimax, ultimate game, linear programming. The game is simple to be useful because most of the game invites players to use logic to achieve profits for himself. Keywords: game theory, mathematics, payoff, matrix, saddle point

International audience ; Game theory is a branch of mathematics aimed at modeling and studying the interactions between several decision-makers (called players) who can have conflicting or common interests. A "game" is essentially a situation in which the benefit or cost reaped by each player gets from an interactive situation does not only depend on its own decisions but also on that taken by the other players. Therefore, in a game, the actions and objectives of the players are tightly coupled. Until very recently, game theory has been used quite marginally in signal processing, noticeable examples being some applications in robust detection and estimation [1], [2] as well as watermarking [3] (in which the watermarking problem is seen as a game between the data embedder and the attacker). However, the real catalyzer of the application of game theory to signal processing has been the blooming of all issues related to networking in general, and distributed networks, in particular. The primary goal of this survey is to provide an all-inclusive, holistic reference on the use of game theory in signal processing application domains. However, we note that, the extensive form, which is used to investigate simple, dynamic situations, will not be discussed in this survey (e.g., see [24] and references therein for more details). The main reason is that, in general, the extensive form is often mathematically less convenient, especially for typical signal processing problems, as advocated by the current state of the signal processing literature, that shows that the dominant model is the strategic form. Defining the corresponding model and providing important results related to the strategic form is the purpose of Section III, which shows how some solution concepts that are inherent to the strategic form can be related to algorithmic aspects. Section IV discusses the coalition form. Whereas issues related to the strategic form concentrate on the strategic choices of the individual and what strategies it chooses to reach its ...

This paper presents a succinct review of attempts in the literature to use game theory to model decision-making scenarios relevant to defence applications. Game theory has been proven as a very effective tool in modelling the decision-making processes of intelligent agents, entities, and players. It has been used to model scenarios from diverse fields such as economics, evolutionary biology, and computer science. In defence applications, there is often a need to model and predict the actions of hostile actors, and players who try to evade or out-smart each other. Modelling how the actions of competitive players shape the decision making of each other is the forte of game theory. In past decades, there have been several studies that applied different branches of game theory to model a range of defence-related scenarios. This paper provides a structured review of such attempts, and classifies existing literature in terms of the kind of warfare modelled, the types of games used, and the players involved. After careful selection, a total of 29 directly relevant papers are discussed and classified. In terms of the warfares modelled, we recognise that most papers that apply game theory in defence settings are concerned with Command and Control Warfare, and can be further classified into papers dealing with (i) Resource Allocation Warfare (ii) Information Warfare (iii) Weapons Control Warfare, and (iv) Adversary Monitoring Warfare. We also observe that most of the reviewed papers are concerned with sensing, tracking, and large sensor networks, and the studied problems have parallels in sensor network analysis in the civilian domain. In terms of the games used, we classify the reviewed papers into papers that use non-cooperative or cooperative games, simultaneous or sequential games, discrete or continuous games, and non-zero-sum or zero-sum games. Similarly, papers are also classified into two-player, three-player or multi-player game based papers. We also explore the nature of players and the construction of payoff ...

International audience ; Game theory is a branch of mathematics aimed at modeling and studying the interactions between several decision-makers (called players) who can have conflicting or common interests. A "game" is essentially a situation in which the benefit or cost reaped by each player gets from an interactive situation does not only depend on its own decisions but also on that taken by the other players. Therefore, in a game, the actions and objectives of the players are tightly coupled. Until very recently, game theory has been used quite marginally in signal processing, noticeable examples being some applications in robust detection and estimation [1], [2] as well as watermarking [3] (in which the watermarking problem is seen as a game between the data embedder and the attacker). However, the real catalyzer of the application of game theory to signal processing has been the blooming of all issues related to networking in general, and distributed networks, in particular. The primary goal of this survey is to provide an all-inclusive, holistic reference on the use of game theory in signal processing application domains. However, we note that, the extensive form, which is used to investigate simple, dynamic situations, will not be discussed in this survey (e.g., see [24] and references therein for more details). The main reason is that, in general, the extensive form is often mathematically less convenient, especially for typical signal processing problems, as advocated by the current state of the signal processing literature, that shows that the dominant model is the strategic form. Defining the corresponding model and providing important results related to the strategic form is the purpose of Section III, which shows how some solution concepts that are inherent to the strategic form can be related to algorithmic aspects. Section IV discusses the coalition form. Whereas issues related to the strategic form concentrate on the strategic choices of the individual and what strategies it chooses to reach its objective, the coalition form is typically concerned about options available to subsets of players (cooperative groups or coalitions), what cooperative coalitions can form, and how the coalition utility is divided among its members. In practice, for a given signal processing problem, the structure of the problem at hand and the practical constraints associated with it will say if the strategic or coalition form is the most suited one. For example, it may occur that both forms are acceptable in terms of information assumptions while complexity issues will lead to selecting the strategic form instead of the coalition one.