Relevant bibliographies by topics / Game theory and optimal control

Academic literature on the topic 'Game theory and optimal control'

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Published: 10 December 2022
Last updated: 29 January 2023

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Journal articles on the topic "Game theory and optimal control"

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Xu, Juanjuan, Wei Wang, and Huanshui Zhang. "Game theory approach to optimal control problem with multi-channel control." International Journal of Control, Automation and Systems 13, no. 1 (December 18, 2014): 58–64. http://dx.doi.org/10.1007/s12555-013-0023-y.

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Makhmudova, Sh D., A. D. Makhmudov, and A. N. Urazgalieva. "Sufficient conditions for the existence of equilibrium in the form of Hamilton-Jacobi equations." Bulletin of the National Engineering Academy of the Republic of Kazakhstan 84, no. 2 (June 15, 2022): 183–94. http://dx.doi.org/10.47533/2020.1606-146x.167.

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The article discusses the application of the theory of optimal control for solving Hamilton-Jacob equations with phase constraints. A method for constructing generalized solutions using optimal control problems is proposed. The results and analysis of numerical experiments, conditions for the existence of equilibrium situations in noncooperative differential games of several persons, namely the conditions for the existence of equilibrium situations in noncooperative differential games of several persons, defining the action according to Hamilton, are stated. Necessary conditions in the form of Hamilton-Jacobi equations are obtained. Game theory as an applied mathematical theory is used to understand and explain the mechanisms that are used when people make decisions. The theory contributes to the functioning of the logic of strategic planning and the relationship between individuals. Game theory as a method of applied mathematics is used for behavioral studies in various conditions, and helps understand the behavior of economic agents. The theory has many applications and can be used in different areas such as: strategy games, administration, economics and artificial intelligence research. The article describes a mathematical method for studying optimal situations in game theory.
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Kim, Sungwook. "Sensor Communication Rate Control Scheme Based on Inference Game Approach." International Journal of Distributed Sensor Networks 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/127349.

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In real-life situations, decisions must be made even when limited or uncertain information is available. Therefore, the payoff of an action is not clearly known when the decision is made. Recently, game theory has become a powerful tool for analyzing the interactions between decision makers in many domains. However, the traditional game theory approach assumes that a player belief about the payoff of a strategy taken is accurate. To address this problem, we introduce a new kind of game, called an inference game, and study how degrees of uncertainty of belief about payoffs impact the outcomes of real-world games. To approximate an optimal decision, our proposed inference game model can clarify how to better manage ambiguous information. In this study, we apply our inference game model to the sensor communication paradigm and confirm that our approach achieves better performance than other existing sensor communication schemes in widely diverse Internet of Things (IoT) environments.
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Jadlovská, Anna, and Kamil Hrubina. "Algorithms of optimal control methods for solving game theory problems." Kybernetes 40, no. 1/2 (March 15, 2011): 290–99. http://dx.doi.org/10.1108/03684921111118059.

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Orlando, Paul A., Robert A. Gatenby, and Joel S. Brown. "Cancer treatment as a game: integrating evolutionary game theory into the optimal control of chemotherapy." Physical Biology 9, no. 6 (November 29, 2012): 065007. http://dx.doi.org/10.1088/1478-3975/9/6/065007.

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Chen, Miao Sheng, and Yung Tse Tsai. "Strategy on Energy Capacity Control." Advanced Materials Research 512-515 (May 2012): 1227–30. http://dx.doi.org/10.4028/www.scientific.net/amr.512-515.1227.

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In the past, energy authorities attempted to prevent potential entrants from participating in the energy market. This study posits that this two-stage game theory is insufficient to describe the modern-day situation. Ware (1984) modified the Dixit (1980) model to develop a three-stage game structure. We use this mathematical model to analyze the optimal cost of an energy authority and the strategy of excess capacity.
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Wang, Si Liang. "Dynamic Flow Scheduling in Air Traffic Network Based on Game Theory." Key Engineering Materials 439-440 (June 2010): 977–82. http://dx.doi.org/10.4028/www.scientific.net/kem.439-440.977.

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Recently, many works have employed deterministic strategies in dealt with flow scheduling problem in Air traffic flow management (ATFM). In practice, however, they are proved unreasonable for omitting airline’s preference in ATFM. In this paper, we develop a novel air traffic flow control model based on game theory to solve this problem in air traffic network. In the flow model, a resource (link/time pair in air traffic network) allocation strategy that uses sequential game method to predict traffic allocation is proposed in resource sharing environment. The problem of multiple airlines competes for an optimal route is formulated as a multi-player dynamic game. Through finding the Nash equilibrium solution of the multi-player dynamic game, the optimal flow scheduling is also formed at the same time. The flow model also incorporates many key characteristics of ATFM, such as competitive airlines, allowing multiply flow control strategies and so on. Numerical simulation results show the feasibility of solving the air traffic flow control problem using game theory on the air traffic network.
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Tian, Jin, Liang Yuan, Wendong Xiao, Teng Ran, Jianbo Zhang, and Li He. "Optimal robust control with cooperative game theory for lower limb exoskeleton robot." Nonlinear Dynamics 108, no. 2 (February 10, 2022): 1283–303. http://dx.doi.org/10.1007/s11071-022-07219-7.

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Li, Bowen, Hua Li, Qiubai Sun, and Rongjian Lv. "Optimal Control of False Information Clarification System under Major Emergencies Based on Differential Game Theory." Computational Intelligence and Neuroscience 2022 (September 23, 2022): 1–19. http://dx.doi.org/10.1155/2022/7291735.

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To further study the issue of false information classification on social platforms after major emergencies, this study regards opinion leaders and Internet users as a false-information classification system and constructs three differential game models of decentralized, centralized, and subsidized decision-making based on optimal control and differential game theory. Comparison analyses and numerical simulations of optimal equilibrium strategies and the optimal benefit between opinion leaders and Internet users, the optimal trajectory and the steady-state value of the total volume of real information, and the optimal benefit of the false information clarification system are carried out. It is found that under centralized decision-making, equilibrium strategy and total benefit of opinion leaders and Internet users, system total benefit, and total volume of real information can achieve Pareto optimality. Although subsidized decision-making fails to achieve Pareto optimality, with opinion leaders providing cost subsidies for Internet users, it is possible to reach relative Pareto improvement compared with decentralized decision-making.
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FALCONE, M. "NUMERICAL METHODS FOR DIFFERENTIAL GAMES BASED ON PARTIAL DIFFERENTIAL EQUATIONS." International Game Theory Review 08, no. 02 (June 2006): 231–72. http://dx.doi.org/10.1142/s0219198906000886.

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In this paper we present some numerical methods for the solution of two-persons zero-sum deterministic differential games. The methods are based on the dynamic programming approach. We first solve the Isaacs equation associated to the game to get an approximate value function and then we use it to reconstruct approximate optimal feedback controls and optimal trajectories. The approximation schemes also have an interesting control interpretation since the time-discrete scheme stems from a dynamic programming principle for the associated discrete time dynamical system. The general framework for convergence results to the value function is the theory of viscosity solutions. Numerical experiments are presented solving some classical pursuit-evasion games.
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Dissertations / Theses on the topic "Game theory and optimal control"

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Shrestha, Bikash. "An Engage or Retreat Differential Game with Two Targets." Wright State University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=wright1503319559060634.

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Chandrasekar, Swathi. "An Engage or Retreat differential game with Mobile Agents." Wright State University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=wright1503716818890551.

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Reimann, Johan Michael. "Using Multiplayer Differential Game Theory to Derive Efficient Pursuit-Evasion Strategies for Unmanned Aerial Vehicles." Diss., Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/16151.

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In recent years, Unmanned Aerial Vehicles (UAVs) have been used extensively in military conflict situations to execute intelligence, surveillance and reconnaissance missions. However, most of the current UAV platforms have limited collaborative capabilities, and consequently they must be controlled individually by operators on the ground. The purpose of the research presented in this thesis is to derive algorithms that can enable multiple UAVs to reason about the movements of multiple ground targets and autonomously coordinate their efforts in real-time to ensure that the targets do not escape. By improving the autonomy of multivehicle systems, the workload placed on the command and control operators is reduced significantly. To derive effective adversarial control algorithms, the adversarial scenario is modeled as a multiplayer differential game. However, due to the inherent computational complexity of multiplayer differential games, three less computationally demanding differential pursuit-evasion game-based algorithms are presented. The purpose of the algorithms is to quickly derive interception strategies for a team of autonomous vehicles. The algorithms are applicable to scenarios with different base assumptions, that is, the three algorithms are meant to complement one another by addressing different types of adversarial problems.
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Alam, Assad. "Fuel-Efficient Distributed Control for Heavy Duty Vehicle Platooning." Licentiate thesis, KTH, Skolan för elektro- och systemteknik (EES), 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-42378.

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Freight transport demand has escalated and will continue to do so as economiesgrow. As the traffic intensity increases, the drivers are faced with increasinglycomplex tasks and traffic safety is a growing issue. Simultaneously, fossil fuel usageis escalating. Heavy duty vehicle (HDV) platooning is a plausible solution to theseissues. Even though there has been a need for introducing automated HDV platooningsystems for several years, they have only recently become possible to implement.Advancements in on-board and external technology have ushered in new possibilitiesto aid the driver and enhance the system performance. Each vehicle is able to serveas an information node through wireless communication; enabling a cooperativenetworked transportation system. Thereby, vehicles can semi-autonomously travel atshort intermediate spacings, effectively reducing congestion, relieving driver tension,improving fuel consumption and emissions without compromising safety. This thesis presents contributions to a framework for the design and implementation of HDV platooning. The focus lies mainly on establishing and validating realconstraints for fuel optimal control for platooning vehicles. Nonlinear and linearvehicle models are presented together with a system architecture, which dividesthe complex problem into manageable subsystems. The fuel reduction potentialis investigated through simulation models and experimental results derived fromstandard vehicles traveling on a Swedish highway. It is shown through analyticaland experimental results that it is favorable with respect to the fuel consumption tooperate the vehicles at a much shorter intermediate spacing than what is currentlydone in commercially available systems. The results show that a maximum fuelreduction of 4.7–7.7 % depending on the inter-vehicle time gap, at a set speedof 70 km/h, can be obtained without compromising safety. A systematic designmethodology for inter-vehicle distance control is presented based on linear quadraticregulators (LQRs). The structure of the controller feedback matrix can be tailoredto the locally available state information. The results show that a decentralizedcontroller gives good tracking performance, a robust system and lowers the controleffort downstream in the platoon. It is also shown that the design methodologyproduces a string stable system for an arbitrary number of vehicles in the platoon,if the vehicle configurations and the LQR weighting parameters are identical for theconsidered subsystems. With the results obtained in this thesis, it is argued that a vast fuel reductionpotential exists for HDV platooning. Present commercial systems can be enhancedsignificantly through the introduction of wireless communication and decentralizedoptimal control.
QC 20111012
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Aduba, Chukwuemeka Nnabuife. "N-Player Statistical Nash Game Control: M-th Cost Cumulant Optimization." Diss., Temple University Libraries, 2014. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/298838.

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Electrical and Computer Engineering
Ph.D.
Game theory is the study of tactical interactions involving conflicts and cooperations among multiple decision makers called players with applications in diverse disciplines such as economics, biology, management, communication networks, electric power systems and control. This dissertation studies a statistical differential game problem where finite N players optimize their system performance by shaping the distribution of their cost function through cost cumulants. This research integrates game theory with statistical optimal control theory and considers a statistical Nash non-cooperative nonzero-sum game for a nonlinear dynamic system with nonquadratic cost functions. The objective of the statistical Nash game is to find the equilibrium solution where no player has the incentive to deviate once other players maintain their equilibrium strategy. The necessary condition for the existence of the Nash equilibrium solution is given for the m-th cumulant cost optimization using the Hamilton-Jacobi-Bellman (HJB) equations. In addition, the sufficient condition which is the verification theorem for the existence of Nash equilibrium solution is given for the m-th cumulant cost optimization using the Hamilton-Jacobi-Bellman (HJB) equations. However, solving the HJB equations even for relatively low dimensional game problem is not trivial, we propose to use neural network approximate method to find the solution of the HJB partial differential equations for the statistical game problem. Convergence proof of the neural network approximate method solution to exact solution is given. In addition, numerical examples are provided for the statistical game to demonstrate the applicability of the proposed theoretical developments.
Temple University--Theses
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Raiss, El Fenni Mohammed. "Opportunistic spectrum usage and optimal control in heterogeneous wireless networks." Phd thesis, Université d'Avignon, 2012. http://tel.archives-ouvertes.fr/tel-00907120.

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The present dissertation deals with how to use the precious wireless resources that are usually wasted by under-utilization of networks. We have been particularly interested by all resources that can be used in an opportunistic fashion using different technologies. We have designed new schemes for better and more efficient use of wireless systems by providing mathematical frameworks. In the first part, We have been interested in cognitive radio networks, where a cellular service provider can lease a part of its resources to secondary users or virtual providers. In the second part, we have chosen delay-tolerant networks as a solution to reduce the pressure on the cell traffic, where mobile users come to use available resources effectively and with a cheaper cost. We have focused on optimal strategy for smartphones in hybrid wireless networks. In the last part, an alternative to delay-tolerant networks, specially in regions that are not covered by the cellular network, is to use Ad-hoc networks. Indeed, they can be used as an extension of the coverage area. We have developed a new analytical modeling of the IEEE 802.11e DCF/EDCF. We have investigated the intricate interactions among layers by building a general cross-layered framework to represent multi-hop ad hoc networks with asymmetric topology and traffic
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Gaddoni, Giacomo. "Modeling of Evolutionary Cancer Dynamics and Optimal Treatment via Dynamic Programming." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021.

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Cancer is one of the biggest challenges in healthcare. Fast diagnosis and personalized pharmacological therapies are essential for lowering the mortality rate. In this thesis, we propose a general-purpose model for cancer and an optimal control strategy to minimize its volume. Firstly, we analyze the literature about cancer in the System and Control community and produce a taxonomy of cancer typologies. We identify four main behaviors arising in these models: growth, mutation, migration, and drug response. After this preliminary analysis, we propose a cancer treatment model based on Ordinary Differential Equations (ODEs) and Evolutionary Game Theory, that captures these dynamics more generally. ODEs provide a framework for lumped-parameters representations, and Evolutionary Game Theory provides tools to describe competitive behaviors typical of these cell populations. Starting from this taxonomy, we chose a model representable with a 2-node graph that expressed all the dynamics of cancer processes. We studied the model, discretized it, and applied an optimal control method based on Differential Dynamic Programming (DDP). Bounded and unbounded DDP were ineffective. It was necessary to introduce regularized DDP via adaptive shift. With this algorithm, the results are promising: the system is successfully stabilized in the origin. It is also possible to control the system, driving it between two equilibria, tracking a demanded trajectory. Most of the testing was done in MATLAB. Then, the project was ported to Python. This was done to facilitate future expansion of the model and control strategies through scientific analysis toolboxes and frameworks.
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Fu, Guanxing. "Maximum Principle for Reflected BSPDE and Mean Field Game Theory with Applications." Doctoral thesis, Humboldt-Universität zu Berlin, 2018. http://dx.doi.org/10.18452/19248.

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Diese Arbeit behandelt zwei Gebiete: stochastische partielle Rückwerts-Differentialgleichungen (BSPDEs) und Mean-Field-Games (MFGs). Im ersten Teil wird über eine stochastische Variante der De Giorgischen Iteration ein Maximumprinzip für quasilineare reflektierte BSPDEs (RBSPDEs) auf allgemeinen Gebieten bewiesen. Als Folgerung erhalten wir ein Maximumprinzip für RBSPDEs auf beschränkten, sowie für BSPDEs auf allgemeinen Gebieten. Abschließend wird das lokale Verhalten schwacher Lösungen untersucht. Im zweiten Teil zeigen wir zunächst die Existenz von Gleichgewichten in MFGs mit singulärer Kontrolle. Wir beweisen, dass die Lösung eines MFG ohne Endkosten und ohne Kosten in der singulären Kontrolle durch die Lösungen eines MFGs mit strikt regulären Kontrollen approximiert werden kann. Die vorgelegten Existenz- und Approximationsresultat basieren entscheidend auf der Wahl der Storokhod M1 Topologie auf dem Raum der Càdlàg-Funktion. Anschließend betrachten wir ein MFG optimaler Portfolioliquidierung unter asymmetrischer Information. Die Lösung des MFG charakterisieren wir über eine stochastische Vorwärts-Rückwärts-Differentialgleichung (FBSDE) mit singulärer Endbedingung der Rückwärtsgleichung oder alternativ über eine FBSDE mit endlicher Endbedingung, jedoch singulärem Treiber. Wir geben ein Fixpunktargument, um die Existenz und Eindeutigkeit einer Kurzzeitlösung in einem gewichteten Funktionenraum zu zeigen. Dies ermöglicht es, das ursprüngliche MFG mit entsprechenden MFGs ohne Zustandsendbedinung zu approximieren. Der zweite Teil wird abgeschlossen mit einem Leader-Follower-MFG mit Zustandsendbedingung im Kontext optimaler Portfolioliquidierung bei hierarchischer Agentenstruktur. Wir zeigen, dass das Problem beider Spielertypen auf singuläre FBSDEs zurückgeführt werden kann, welche mit ähnlichen Methoden wie im vorangegangen Abschnitt behandelt werden können.
The thesis is concerned with two topics: backward stochastic partial differential equations and mean filed games. In the first part, we establish a maximum principle for quasi-linear reflected backward stochastic partial differential equations (RBSPDEs) on a general domain by using a stochastic version of De Giorgi’s iteration. The maximum principle for RBSPDEs on a bounded domain and the maximum principle for BSPDEs on a general domain are obtained as byproducts. Finally, the local behavior of the weak solutions is considered. In the second part, we first establish the existence of equilibria to mean field games (MFGs) with singular controls. We also prove that the solutions to MFGs with no terminal cost and no cost from singular controls can be approximated by the solutions, respectively control rules, for MFGs with purely regular controls. Our existence and approximation results strongly hinge on the use of the Skorokhod M1 topology on the space of càdlàg functions. Subsequently, we consider an MFG of optimal portfolio liquidation under asymmetric information. We prove that the solution to the MFG can be characterized in terms of a forward backward stochastic differential equation (FBSDE) with possibly singular terminal condition on the backward component or, equivalently, in terms of an FBSDE with finite terminal value, yet singular driver. We apply the fixed point argument to prove the existence and uniqueness on a short time horizon in a weighted space. Our existence and uniqueness result allows to prove that our MFG can be approximated by a sequence of MFGs without state constraint. The final result of the second part is a leader follower MFG with terminal constraint arising from optimal portfolio liquidation between hierarchical agents. We show the problems for both follower and leader reduce to the solvability of singular FBSDEs, which can be solved by a modified approach of the previous result.
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Pitcher, Ashley Brooke. "Mathematical modelling and optimal control of constrained systems." Thesis, University of Oxford, 2009. http://ora.ox.ac.uk/objects/uuid:044a26ab-99dc-4b34-b4a3-04e5c0d61ba0.

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This thesis is concerned with mathematical modelling and optimal control of constrained systems. Each of the systems under consideration is a system that can be controlled by one of the variables, and this control is subject to constraints. First, we consider middle-distance running where a runner's horizontal propulsive force is the control which is constrained to be within a given range. Middle-distance running is typically a strategy-intensive race as slipstreaming effects come into play since speeds are still relatively fast and runners can leave their starting lane. We formulate a two-runner coupled model and determine optimal strategies using optimal control theory. Second, we consider two applications of control systems with delay related to R&D expenditure. The first of these applications relates to the defence industry. The second relates to the pharmaceutical industry. Both applications are characterised by a long delay between initial investment in R&D and seeing the benefits of R&D realised. We formulate models tailored to each application and use optimal control theory to determine the optimal proportion of available funds to invest in R&D over a given time horizon. Third, we consider a mathematical model of urban burglary based on the Short model. We make some modifications to this model including the addition of deterrence due to police officer presence. Police officer density is the control variable, which is constrained due to a finite number of police officers. We look at different control strategies for the police and their effect on burglary hot-spot formation.
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Luo, Yi. "DECISION MAKING UNDER UNCERTAINTY IN DYNAMIC MULTI-STAGE ATTACKER-DEFENDER GAMES." Diss., The University of Arizona, 2011. http://hdl.handle.net/10150/204331.

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This dissertation presents efficient, on-line, convergent methods to find defense strategies against attacks in dynamic multi-stage attacker-defender games including adaptive learning. This effort culminated in four papers submitted to high quality journals and a book and they are partially published. The first paper presents a novel fictitious play approach to describe the interactions between the attackers and network administrator along a dynamic game. Multi-objective optimization methodology is used to predict the attacker's best actions at each decision node. The administrator also keeps track of the attacker's actions and updates his knowledge on the attacker's behavior and objectives after each detected attack, and uses this information to update the prediction of the attacker's future actions to find its best response strategies. The second paper proposes a Dynamic game tree based Fictitious Play (DFP) approach to describe the repeated interactive decision processes of the players. Each player considers all possibilities in future interactions with their uncertainties, which are based on learning the opponent's decision process (including risk attitude, objectives). Instead of searching the entire game tree, appropriate future time horizons are dynamically selected for both players. The administrator keeps tracking the opponent's actions, predicts the probabilities of future possible attacks, and then chooses its best moves. The third paper introduces an optimization model to maximize the deterministic equivalent of the random payoff function of a computer network administrator in defending the system against random attacks. By introducing new variables the transformed objective function becomes concave. A special optimization algorithm is developed which requires the computation of the unique solution of a single variable monotonic equation. The fourth paper, which is an invited book chapter, proposes a discrete-time stochastic control model to capture the process of finding the best current move of the defender. The defender's payoffs at each stage of the game depend on the attacker's and the defender's accumulative efforts and are considered random variables due to their uncertainty. Their certain equivalents can be approximated based on their first and second moments which is chosen as the cost functions of the dynamic system. An on-line, convergent, Scenarios based Proactive Defense (SPD) algorithm is developed based on Differential Dynamic Programming (DDP) to solve the associated optimal control problem.
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Books on the topic "Game theory and optimal control"

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Molloy, Timothy L., Jairo Inga Charaja, Sören Hohmann, and Tristan Perez. Inverse Optimal Control and Inverse Noncooperative Dynamic Game Theory. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-93317-3.

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Weber, Thomas A. Optimal control theory with applications in economics. Cambridge, Mass: MIT Press, 2011.

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1940-, Feichtinger Gustav, ed. Dynamic economic models and optimal control: Fourth Viennese Workshop on Dynamic Economic Models and Optical [i.e. Optimal] Control, held in Vienna, June 12-14, 1991. Amsterdam: North-Holland, 1992.

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1942-, Jørgensen Steffen, and Zaccour Georges, eds. Optimal control and differential games: Essays in honor of Steffen Jørgensen. Boston: Kluwer Academic Publishers, 2002.

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Game theory for control of optical networks. New York: Birkhäuser, 2012.

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Pavel, Lacra. Game Theory for Control of Optical Networks. Boston: Birkhäuser Boston, 2012. http://dx.doi.org/10.1007/978-0-8176-8322-1.

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1940-, Feichtinger Gustav, ed. Optimal control theory and economic analysis 3: Third Viennese Workshop on Optimal Control Theory and Economic Analysis held in Vienna, May 20-22, 1987. Amsterdam: North Holland, 1988.

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Elliott, Robert J. Viscosity solutions and optimal control. Harlow, Essex, England: Longman Scientific & Technical, 1987.

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1940-, Feichtinger Gustav, Technische Universität Wien. Institut für Ökonometrie und Operations Research., and Österreichische Gesellschaft für Operations Research., eds. Optimal control theory and economic analysis 2: Second Viennese Workshop on Economic Applications of Control Theory, held in Vienna, May 16-18, 1984. Amsterdam: North-Holland, 1985.

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1948-, Capuzzo Dolcetta I., ed. Optimal control and viscosity solutions of Hamilton-Jacobi-Bellman equations. Boston: Birkhäuser, 1997.

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Book chapters on the topic "Game theory and optimal control"

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Sethi, Suresh P. "Differential Games." In Optimal Control Theory, 385–407. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-98237-3_13.

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Ma, Zhongjing, and Suli Zou. "Differential Games." In Optimal Control Theory, 249–75. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-6292-5_6.

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Muros, Francisco Javier. "Coalitional Systems in Optimal Control." In Cooperative Game Theory Tools in Coalitional Control Networks, 41–67. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-10489-4_3.

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Chevalier-Roignant, Benoit, and Lenos Trigeorgis. "Option Games: The Interface Between Optimal Stopping and Game Theory." In Encyclopedia of Systems and Control, 1011–15. London: Springer London, 2015. http://dx.doi.org/10.1007/978-1-4471-5058-9_41.

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Chevalier-Roignant, Benoit, and Lenos Trigeorgis. "Option Games: The Interface Between Optimal Stopping and Game Theory." In Encyclopedia of Systems and Control, 1–5. London: Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-5102-9_41-1.

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Chevalier-Roignant, Benoît, and Lenos Trigeorgis. "Option Games: The Interface Between Optimal Stopping and Game Theory." In Encyclopedia of Systems and Control, 1641–46. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-44184-5_41.

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Chevalier-Roignant, Benoît, and Lenos Trigeorgis. "Option Games: The Interface Between Optimal Stopping and Game Theory." In Encyclopedia of Systems and Control, 1–5. London: Springer London, 2021. http://dx.doi.org/10.1007/978-1-4471-5102-9_41-2.

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Molloy, Timothy L., Jairo Inga Charaja, Sören Hohmann, and Tristan Perez. "Discrete-Time Inverse Optimal Control." In Inverse Optimal Control and Inverse Noncooperative Dynamic Game Theory, 41–96. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-93317-3_3.

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Molloy, Timothy L., Jairo Inga Charaja, Sören Hohmann, and Tristan Perez. "Continuous-Time Inverse Optimal Control." In Inverse Optimal Control and Inverse Noncooperative Dynamic Game Theory, 97–142. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-93317-3_4.

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Taynitskiy, Vladislav, Elena Gubar, and Quanyan Zhu. "Optimal Impulse Control of SIR Epidemics Over Scale-Free Networks." In Game Theory for Networking Applications, 119–29. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-93058-9_8.

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Conference papers on the topic "Game theory and optimal control"

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Yuanzhou Yang, Shaokuan Chen, Rong Huang, Xiao Liang, and Baohua Mao. "Optimal road congestion pricing based on game theory." In 2010 Chinese Control and Decision Conference (CCDC). IEEE, 2010. http://dx.doi.org/10.1109/ccdc.2010.5498410.

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Yang Xinying, Gong Guanghong, Tian Yuan, and Yu Xiaoxia. "Generalized Optimal Game Theory in virtual decision-makings." In 2008 Chinese Control and Decision Conference (CCDC). IEEE, 2008. http://dx.doi.org/10.1109/ccdc.2008.4597668.

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Tamaddoni, Seyed Hossein, Mehdi Ahmadian, and Saied Taheri. "Optimal vehicle stability control design based on preview game theory concept." In 2011 American Control Conference. IEEE, 2011. http://dx.doi.org/10.1109/acc.2011.5991479.

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Jie Wei and Jing Zhao. "Optimal decisions for two assembled products based on game theory." In 2008 Chinese Control and Decision Conference (CCDC). IEEE, 2008. http://dx.doi.org/10.1109/ccdc.2008.4597830.

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Xie, Jiahao, Shucai Huang, Daozhi Wei, and Zhaoyu Zhang. "Sensor Management Method based on Optimal Response Dynamics with Game Theory." In 2021 International Conference on Control Science and Electric Power Systems (CSEPS). IEEE, 2021. http://dx.doi.org/10.1109/cseps53726.2021.00055.

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Xu, Jing, Huizhen Pang, Bingzhe Zhang, Qixian Li, and Yu Huang. "Optimal Scheduling Method of Multi-Energy Hub Systems Based on Bayesian Game Theory." In 2021 40th Chinese Control Conference (CCC). IEEE, 2021. http://dx.doi.org/10.23919/ccc52363.2021.9549860.

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Mondal, Debasish, and Asim Halder. "Nonlinear optimal STATCOM controller based on game theory to improve transient stability." In 2016 2nd International Conference on Control, Instrumentation, Energy & Communication (CIEC). IEEE, 2016. http://dx.doi.org/10.1109/ciec.2016.7513734.

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Ghods, Amir Hosein, and Ashkan Rahimi-Kian. "A game theory approach to optimal coordinated ramp metering and variable speed limits." In 2008 Chinese Control and Decision Conference (CCDC). IEEE, 2008. http://dx.doi.org/10.1109/ccdc.2008.4597276.

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Shen, D., and J. B. Cruz. "An improved game theory based approach to one type of H-infinity optimal control problems." In 2006 American Control Conference. IEEE, 2006. http://dx.doi.org/10.1109/acc.2006.1656463.

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Bewick, S., Ruoting Yang, and Mingjun Zhang. "Embedding evolutionary game theory into an optimal control framework for drug dosage design." In 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2009. http://dx.doi.org/10.1109/iembs.2009.5333520.

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Reports on the topic "Game theory and optimal control"

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Won, Chang-Hee. Characteristics, Nonlinearity of Statistical Control and Relations with Dynamic Game Theory. Fort Belvoir, VA: Defense Technical Information Center, November 2005. http://dx.doi.org/10.21236/ada440472.

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Iyer, R. V., R. Holsapple, and D. Doman. Optimal Control Problems on Parallelizable Riemannian Manifolds: Theory and Applications. Fort Belvoir, VA: Defense Technical Information Center, January 2002. http://dx.doi.org/10.21236/ada455175.

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Yeh, Edmund M. Theory, Design, and Algorithms for Optimal Control of wireless Networks. Fort Belvoir, VA: Defense Technical Information Center, June 2010. http://dx.doi.org/10.21236/ada522224.

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Moin, Parviz, Jeremy A. Templeton, and Meng Wang. Wall Models for Large-Eddy Simulation Based on Optimal Control Theory. Fort Belvoir, VA: Defense Technical Information Center, June 2006. http://dx.doi.org/10.21236/ada451008.

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Jin, Dafeng, Peng Li, Yugong Ruo, Rui Chen, and Keqiang Li. The Study for the Regenerative Braking Strategy Based on the Optimal Control Theory. Warrendale, PA: SAE International, May 2005. http://dx.doi.org/10.4271/2005-08-0407.

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Forero-Alvarado, Santiago, Nicolás Moreno-Arias, and Juan J. Ospina-Tejeiro. Humans Against Virus or Humans Against Humans: A Game Theory Approach to the COVID-19 Pandemic. Banco de la República, May 2021. http://dx.doi.org/10.32468/be.1160.

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Externalities and private information are key characteristics of an epidemic like the Covid-19 pandemic. We study the welfare costs stemming from the incomplete information environment that these characteristics foster. We develop a framework that embeds a game theory approach into a macro SIR model to analyze the role of information in determining the extent of the health-economy trade-off of a pandemic. We apply the model to the Covid-19 epidemic in the US and find that the costs of keeping health information private are between USD $5.9$ trillion and USD $6.7$ trillion. We then find an optimal policy of disclosure and divulgation that, combined with testing and containment measures, can improve welfare. Since it is private information about individuals' health what produces the greatest welfare losses, finding ways to make such information known as precisely as possible, would result in significantly fewer deaths and significantly higher economic activity.
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Ismailova, L. Yu, S. V. Kosikov, V. S. Zaytsev, and I. O. Sleptsov. educational computer game THE ADVENTURES OF THE GUSARIK" OR THE BASIS OF THE THEORY OF THE STATE AND LAW (version 1.0). SIB-Expertise, July 2022. http://dx.doi.org/10.12731/er0577.04072022.

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Abstract:
TRAINING GAME IS DESIGNED TO OBTAIN NEW AND TEST EXISTING KNOWLEDGE IN THE FIELD OF ONE OF THE MOST IMPORTANT LEGAL DISCIPLINES - THEORY OF STATE AND LAW. GAME ALLOWS TO TEST ITS FORCES IN INTERACTIVE MODE IN SOLVING A LARGE NUMBER OF THEORETICAL AND PRACTICAL QUESTIONS. THE STUDENT CAN WORK OUT NEW TOPICS USING NUMEROUS COMMENTS AND CHECK THE RESULTS OF THEIR ASSIMILATION. GAME CHARACTER'S CLUES AND FACIAL EXPRESSIONS MOTIVATE THE PLAYER TO CAREFULLY WORK WITH THE OBJECT AND ALLOW YOU TO INDEPENDENTLY WORK ON TOPICS THAT CAUSED DIFFICULTIES IN THE CONTROL MODE. GAME CONTENT COMPLIES WITH THE PROGRAM OF THE STATE STANDARD IN THE SPECIALTY "LAW." THE MAIN GOAL OF THE GAME IS TO HELP IN HIGHLIGHTING THEORETICAL LEGAL STRUCTURES IN PRACTICAL SITUATIONS, TO DEVELOP THE SKILLS OF LEGAL ANALYSIS OF THE TEXT OF LEGAL NORMS AND LAW ENFORCEMENT DOCUMENTS, AND THEREBY TO INCREASE THE EFFECTIVENESS OF THE APPLICATION OF LAW.IN ADDITION, THE EDucational GAME WILL INTRODUCE PROFESSIONAL LEGAL TERMINOLOGY IN THIS FIELD. THE GAME "THEORY OF STATE AND LAW" CAN BE USEFUL FOR STUDENTS OF LAW UNIVERSITIES AND FACULTIES, PRACTICING LAWYERS AND EVERYONE WISHING TO IMPROVE THEIR QUALIFICATIONS IN THE FIELD OF LAW. CERTAIN SECTIONS OF THE GAME WILL BE USEFUL FOR TRAINING IN THE UNIVERSITY IN LEGAL SPECIALTIES.
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Friedmann, Michael, Charles J. Arntzen, and Hugh S. Mason. Expression of ETEC Enterotoxin in Tomato Fruit and Development of a Prototype Transgenic Tomato for Dissemination as an Oral Vaccine in Developing Countries. United States Department of Agriculture, March 2003. http://dx.doi.org/10.32747/2003.7585203.bard.

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The broad objective of the project was to develop a feasible approach to combat diarrheal disease caused by ETEC through the development of a low-cost oral immunogen in tomato fruit, expressed in the context of a prototype tomato that would answer the shortcomings of plant oral vaccines, especially in terms of produce handling and control of gene escape. Specifically, the goals for Boyce Thompson Institute (BTI) on this project were to develop transgenic tomato lines that express the enterotoxigenic E. coli (ETEC) heat-labile enterotoxin (LT) subunits A and/or B for use in oral edible vaccines, and to optimize expression and assembly of these antigens in tomato fruits.LT-B is a useful vaccine antigen against ETEC disease, since antibodies against LT-B can prevent binding and delivery of the holotoxinLT. Mutant forms of the toxic LT-A subunit that have reduced toxicity can be co-expressed and assembled with LT-Bpentamers to form mutant LT (mLT) complexes that could be used as mucosaladjuvants for other oral vaccines. Work on the project is continuing at Arizona State University, after Dr. Mason moved there in August 2002. A number of approaches were taken to ensure the expression of both subunits and bring about their assembly inside the transgenic fruits. Initially, expression was driven by the fruit-specific E-8 promoter for LT-B and the constitutive CaMV 35S promoter for LT-A(K63). While LT-B accumulated up to 7 µg per gram ripe fruit, assembled LT-K63 was only 1 µg per gram. Since promoter activities for the two genes likely differed in cell type and developmental stage specificity, the ratios of A and B subunits was not optimal for efficient assembly in all cells. In order to maximize the chance of assembly of mLT in fruit, we focused on constructs in which both genes are driven by the same promoter. These included co-expression plasmids using the 35S promoter for both, while switching to attenuated mLTs (LT-R72 and LT-G192) that have shown greater potential for oral adjuvanticity than the initial LT-K63, and thus are better candidates for a plant-derived adjuvant. Other, more novel approaches were then attempted, including several new vectors using the tomato fruit-specific E8 promoter driving expression of both LT-B and mutant LT-A, as well as a dicistronic construct for co-expression of both LT-B and mutant LT-A genes from a single promoter, and a geminivirusreplicon construct. We describe in the Appendix the results obtained in transgenic tomato lines transformed with these constructs. Overall, each contributed to enhanced expression levels, but the assembly itself of the holotoxin to high levels was not observed in the fruit tissues. The Israeli lab’s specific objective was to develop transgenic tomato lines expressing the LTholotoxin antigen bearing attributes to prevent gene escape (male sterility and orange fruit color) and to improve the dissemination of the oral vaccine (long shelf-life tomato cherry fruit or tomato processing background). Breeding lines bearing a number of attributes to prevent gene escape were developed by combining material and backcrossing either to a tomato cherry background, or two different processing backgrounds. Concomitantly, (these lines can be utilized for the creation of any future oral vaccine or other therapeutic-expressing tomato, either by crosses or transformation), the lines were crossed to the holotoxin-expressing tomatoes received from the United States, and this transgenic material was also incorporated into the backcrossing programs. To date, we have finalized the preparation of the cherry tomato material, both non-transgenic (bearing all the desired attributes), and transgenic, expressing the holotoxin. The level of expression of LT-B in the cherry fruits was comparable to the original transgenic tomatoes. Since it was not higher, this would necessitate the consumption of more fruits to reach a desired dose. A final backcross has been made for both the non-transgenic and the transgenic material in the processing lines. Auxin sprays resulted in high percentages of fruit set, but the processing genotypes gave many puffed fruits.
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