In modern computer games, `bots' - Intelligent realistic agents play a prominent role in success of a game in the market. Typically, bots are modeled using finite-state machine and then programmed via simple conditional statements which are hard-coded in bots logic. Since these bots have become quite predictable to an experienced games' player, a player might lose interest in the game. We propose the use of a game theoretic based learning rule called Fictitious Play for improving behavior of these computer game bots which will make them less predictable and hence, more enjoyable to a game player.

M.Sc. (Mathematics) / This dissertation describes the solution toa specific logical problem, the satisfiability problem, in a logic of games called Alternating-time Temporal Logic (ATL). Computation Tree Logic (CTL) is a discrete branching-time temporal logic for reasoning about labelled transition systems. ATL extends CTL to describe gametheoretic situations, where multiple agents together determine the evolution of the system. In particular, ATL explicitly provides for describing the abilities of coalitions of agents in such systems. Weprovide an automata-based decision procedure for ATL by translating the satisfiability problem for an ATL formula to the nonemptiness problem for an Alternating Biichi 'free Automaton. The key result that enables this translation is a oundedbranching tree model theorem for ATL, proving that a satisfiable formula is also satisfiable in a tree model of bounded branching degree. In terms of complexity, we show that satisfiability in ATL is complete for exponential time, which agrees with the corresponding complexity result for the fragment CTL. Closely related to ATL is an independently developed family of modal logics, the Coalition Logics. The presented results also provide a satisfiability procedure for Extended Coalition Logic interpreted over strongly playable coalition models. The structure of the dissertation is as follows: • Chapter 1 is an introduction to the topic, provides an overview of the results and a preview of the dissertation. • Chapter 2 presents some mathematical preliminaries regarding trees, automata, fixed points and game theory. • Chapter 3 discusses CTL and in particular an automata-based satisfiability procedure for CTL. • Chapter 4 introduces Alternating-time Temporal Logic (ATL) as a logic of games. • Chapter 5 contains the main results of the dissertation: first we prove a boundedbranching tree model property for ATL. Then the construction of the required automaton for satisfiability checking is described. • Chapter 6 relates the present work to some other logics of games, and in particular the Coalition Logics. • Chapter 7 finalises the dissertation with a conclusion and a look at some future research directions that might be pursued following the present work.

Doctorat en sciences sociales, politiques et économiques / info:eu-repo/semantics/nonPublished

Wireless sensor networks are emerging as effective tools in the gathering and dissemination of data. They can be applied in many fields including health, environmental monitoring, home automation and the military. Like all other computing systems it is necessary to include security features, so that security sensitive data traversing the network is protected. However, traditional security techniques cannot be applied to wireless sensor networks. This is due to the constraints of battery power, memory, and the computational capacities of the miniature wireless sensor nodes. Therefore, to address this need, it becomes necessary to develop new lightweight security protocols. This dissertation focuses on designing a suite of lightweight trust-based security mechanisms and a cooperation enforcement protocol for wireless sensor networks. This dissertation presents a trust-based cluster head election mechanism used to elect new cluster heads. This solution prevents a major security breach against the routing protocol, namely, the election of malicious or compromised cluster heads. This dissertation also describes a location-aware, trust-based, compromise node detection, and isolation mechanism. Both of these mechanisms rely on the ability of a node to monitor its neighbors. Using neighbor monitoring techniques, the nodes are able to determine their neighbors’ reputation and trust level through probabilistic modeling. The mechanisms were designed to mitigate internal attacks within wireless sensor networks. The feasibility of the approach is demonstrated through extensive simulations. The dissertation also addresses non-cooperation problems in multi-user wireless sensor networks. A scalable lightweight enforcement algorithm using evolutionary game theory is also designed. The effectiveness of this cooperation enforcement algorithm is validated through mathematical analysis and simulation. This research has advanced the knowledge of wireless sensor network security and cooperation by developing new techniques based on mathematical models. By doing this, we have enabled others to build on our work towards the creation of highly trusted wireless sensor networks. This would facilitate its full utilization in many fields ranging from civilian to military applications.

Occasionally, a part of the budget of a city, company or other entity has to be allocated among its parts in the form of subsidies or other contributions. The main objective of such an entity is to find such a set of criteria and such a set of their relative weights that estimate the expected cost best. The objective of a sub-entity is subsidy maximization by influencing the criteria and their weights. From this reason, the best budget splitting is a relative term. From the mathematical point of view, such a problem belongs to mathematical optimization or mathematical programming. In this thesis, five quantitative methods are presented. Two of them set the weights without the participation of decision makers. The first allocation method is based on multiple-criteria decision-making and the second one on data envelopment analysis. Together with them, a different mathematical model with maximum and minimum weights for the set of criteria is presented. Two its modifications are discussed too. As the only one presented multi-criteria mathematical model is based on maximization of the relative and absolute profit simultaneously. The aim of this work is to study the known mathematical models for subsidy allocation problem, to invent new ones, to choose suitable ones and subsequently to implement the suitable ones into a standalone GUI application created in the Matlab environment. The presented application proposes several allocation possibilities according to different selected models using mathematical functions taken from Matlab. This user-friendly application is executable on common computers and can be used at the Magistrate of the City of Prague as a support tool in voting decision. Moreover, this application can be extended to new methods or program functions. The selected quantitative methods are used for the budget allocation problem among the city districts for real data of the City of Prague. Experimental results are discussed.

The purpose of this thesis is to provide a beginning graduate student in mathematics with the general theory underlying competition between rational, intelligent opponents. This competition can be described as a game of opposing strategies; hence, the name game theory.

To deter is central for strategic thinking. Some of the more astute observations regarding the dynamics of deterrence were made during the Cold War by game theorists. This set the stage for how deterrence has come to be studied. A strong methodological element like the research on deterrence’s reliance on game theory requires examination in order to understand what sort of knowledge it actually yields. What sort of knowledge does one acquire when deterrence is viewed through game theoretic models? How do they inform us about the phenomenon of deterrence? To understand the nature of a phenomenon through models requires idealization, which in turn presupposes assumptions. This licentiate thesis investigates the type of knowledge we attain when approaching deterrence from a game theoretic perspective. The two articles presented address two separate but related issues. The first article reviews a debate regarding which deterrence model best capture the phenomena of deterrence, i.e. how models can be compared to one and other. The article presents a framework for comparing models and then appraises how these different deterrence models inform us about deterrence. The second article uses one of the more central deterrence models in order to evaluate how and to what extent the naval operation Atalanta managed to deter the Somali piracy.

This thesis explores a game-theoretical approach for underwater environmental monitoring applications. We first apply game-theoretical algorithm to multi-agent resource coverage problem in drifting environments. Furthermore, existing utility design and learning process of the algorithm are modified to fit specific constraints of underwater exploration/monitoring tasks. The revised approach can take the real scenario of underwater monitoring applications such as the effect of sea current, previous knowledge of the resource and occasional communications between agents into account, and adapt to them to reach better performance. As the motivation of this thesis is from real applications, in this work we emphasize highly on implementation phase. A ROS-Gazebo simulation environment was created for preparation of actual tests. The algorithms are implemented in simulating both the dynamics of vehicles and the environment. After that, a multi-agent underwater autonomous robotic system was developed for hardware test in real settings with local controllers to make their own decisions. These systems are used for testing above mentioned algorithms and future development of other underwater projects. After that, other works related to robotics during this thesis will be briefly mentioned, including contributions in MBZIRC robotics competition and distributed control of UAVs in an adversarial environment.

Multi-player interactions and vertical relationships in the U.S. containerized-import shipment market are investigated using game theory approaches. Bi-level programming problems (BLPP) are built to capture the hierarchy structure of the container shipping industry, whereas the ocean carriers (OC) are considered as the market leader. For a case study with five players from several levels of the shipment chain, 16 BLPPs are built to analyze the 32 coalition possibilities. Two routes are compared: The West Coast route (WCR) includes one terminal (P1) and one railroad (R); the East Coast route (ECR) includes a second terminal (P2) and the Panama Canal (PC). The impact of Panama Canal expansion is investigated by comparing scenarios with different assumptions of vessel size. Capacity constraints at port terminals are also analyzed by assuming different capacity levels. The grand coalition of the five players is found to be very unstable because of the unavoidable competition within the coalition; hence, following games are further created, supposing the grand coalition could not form. Model results indicate the OC prefers to form an East Coast Coalition (ECC) with East Coast players if the grand coalition could not form. Sensitivity analyses on some parameter values for the grand coalition and for the ECC bring some interesting findings. With higher cargo values, the WCR becomes more appealing because of its quicker delivery time and lower inventory costs compared with the ECR. The Panama Canal expansion will improve market power and profit shares for the East Coast players if the canal operator could increase its competitive price more than the increase of costs. Generally, a player will gain more market power if its cost could be reduced. A player's upper bound rate is a reflection of its relative market power. But in a complicated market characterized with various cooperation-competition strategies and an ambiguous definition of partners and competitors, the impact of a player's upper bound rate on the market power structure could not be easily explained. For future research, the challenge mainly lies on the large number of BLPPs that need to be constructed and solved in order to study more players.

What distinguishes a meaningless utterance from a meaningful term?  While one might say that, within the context of Ruth Millikan\'s teleosemantics, it is a term\'s having a proper function that distinguishes it from a meaningless utterance, I propose that the distinction can be made with reference to the history of the term.  Using evolutionary game theory, I offer a way to clarify the distinction between the meaningless and the meaningful.  I reject the possibility of correlating meaning with an evolutionarily stable strategy as this does not seem to be consistent with how communication works or with Millikan\'s theory.  Instead, when a term has meaning, the function category of that term corresponds to an evolutionarily stable state composed of both speaker and hearer strategies. / Master of Arts