Dynamic Game Theory Research Articles

Model predictive and non-cooperative dynamic game fault recovery control strategies for a network of unmanned underwater vehicles

ABSTRACTIn this paper, the problem of control and fault recovery for a team of autonomous underwater vehicles in the presence of loss of effectiveness (LOE) actuator faults is addressed. Towards this end, two different fault recovery control strategies based on the model predictive control technique as well as the dynamic game theory are proposed and developed. Given the allowable information that can be exchanged among the agents, both centralised and semi-decentralised recovery control schemes are considered and their associated corresponding fault recovery strategies are developed. The proposed active fault recovery control strategies incorporate both the online inaccurate as well as delayed actuator fault estimates to reconfigure the nominal (healthy state) controllers. The effectiveness of the proposed semi-decentralised fault recovery control schemes is quantitatively investigated through extensive simulation case studies considering various LOE actuator fault severities in one or more unmanned vehicles as well as fault detection and isolation module imperfections such as fault estimation error and time delays in detecting the faults. The simulation results demonstrate and illustrate that our proposed semi-decentralised recovery control scheme can maintain acceptable degraded tracking and formation keeping performance of both the faulty and healthy agents in the team with lower computational and communication bandwidth requirements as well as lower or fairly close control effort cost as compared to the centralised control recovery scheme.

Pareto optimal layout of multistatic radar

Layouts influence the performance of location accuracy greatly in multistatic radar. The layout in classical regular shape may not be an excellent choice. In this paper, Pareto optimal layout of multistatic radar is proposed based on dynamic game theory. The available volume associated with the Cramer-Rao lower bound (CRLB) of location accuracy is proposed as the utility metric to evaluate the performance of the layout. Simulation results show that different initial layouts may lead to different final layouts. Although these final layouts are different they are all Pareto optimal and similar in performance.

Inverse Reinforcement Learning for Identification in Linear-Quadratic Dynamic Games

The theory of dynamic games has received considerable attention in a wide range of fields. While great effort has been made to develop new algorithms for finding Nash equilibria in dynamic games, the identification of cost functions has received little attention. We present an identification algorithm for linear quadratic dynamic games, a framework which can be applied in the field of shared control between a human and an automatic controller. In this application, the cost function describing human behavior is identified, taking into account the influence of the automation. Furthermore, we consider that human movement underlies certain variability by using a probabilistic Inverse Reinforcement Learning approach. As identification is performed in a single optimization step, the proposed method is suited for real-time applications. A simulation example shows that the algorithm successfully identifies the cost function of the first player which—in combination with the second player—reproduces the observed system output.

H∞ - Optimal Control over erasure channel

In this paper, the optimal H∞ control of a linear time invariant (LTI) networked control system (NCS) over a lossy network is analyzed. Specifically we consider a TCP-like data network where packet drops are modelled using a two-state Markov process. By employing the theory of dynamic games, a state-feedback H∞ controller is obtained. It is shown that, subjected to a suitable H∞ disturbance attenuation level and suitable packet loss probabilities, such a controller exists for both finite and infinite horizon cases. We also show the asymptotic stability of the NCS in the mean-square sense. Finally a numerical example is presented to demonstrate our work.

A genetic approach to the rock-paper-scissors game

Polymorphisms are usually associated with defenses and mating strategies, affecting the individual’s fitness. Coexistence of different morphs is, therefore, not expected, since the fittest morph should outcompete the others. Nevertheless, coexistence is observed in many natural systems. For instance, males of the side-blotched lizards (Uta stansburiana) present three morphs with throat colors orange, yellow and blue, which are associated with mating strategies and territorial behavior. The three male morphs compete for females in a system that is well described by the rock-paper-scissors dynamics of game theory. Previous studies have modeled the lizards as hermaphroditic populations whose individual’s behavior were determined only by their phenotypes. Here we consider an extension of this dynamical system where diploidy and sexual reproduction are explicitly taken into account. Similarly to the lizards we represent the genetic system by a single locus with three alleles, o, y, and b in a diploid chromosome with dominance of o over y and of y over b. We show that this genotypic description of the dynamics results in the same equilibrium phenotype frequencies as the phenotypic models, but affects the stability of the system, changing the parameter region where coexistence of the three morphs is possible in a rock-paper-scissors game.

Dynamic Game on Carbon Emission Reduction in Intermodal Supply Chain

With the development of international trade, intermodal operations have become more and more important in goods transportation, in order to show the effect of carbon emission tax on a marine-land intermodal supply chain, this paper use dynamic game theory to get a sub-game Nash equilibrium, and the result of this paper show that the carbon emission tax will lead to sea transport and land transport to reduce the carbon emission of every goods, But the carbon tax is not necessarily guaranteed to reduce the total amount of carbon emissions. meanwhile, one part’s reduction of carbon emission may incentive the other part to reduce carbon emission.

Game theory and dynamic programming in alternate games

We present an analysis of different classes of alternate games from different perspectives, including game theory, logic, bounded rationality and dynamic programming. In this paper we review some of these approaches providing a methodological framework which combines ideas from all of them, but emphasizing dynamic programming and game theory. In particular we study the relationship between games in discrete and continuous time and state space and how the latter can be understood as the limit of the former. We show how in some cases the Hamilton-Jacobi-Bellman equation for the discrete version of the game leads to a corresponding HJB partial differential equation for the continuous case and how this procedure allow us to obtain useful information about optimal strategies. This analysis yields another way to compute subgame perfect equilibrium.

A Cloud Service Broker Based on Dynamic Game Theory for Bilateral SLA Negotiation in Cloud Environment

In recent years, with the development of cloud computing, more and more service providers appear, making the cloud computing market more open and competitive. However, it is difficult for service consumers to choose the most suitable service provider for their own, especially for the service providers to provide the best service in the negotiated price, while the service providers and the service consumers themselves can't automatically negotiate, thus in this paper, we propose a cloud service broker framework based on dynamic game theory for bilateral SLA negotiation in cloud environment, aiming for successful negotiation among participators. This paper also proposes a Nash equilibrium point and a satisfaction degree difference algorithm, aiming to find the optimal value of SLA attributes (price and bandwidth) at the minimum satisfaction degree difference among the participators. Experimental results show that the service consumers and the service providers are able to achieve the same satisfaction degree on price and bandwidth.

Detecting the Collapse of Cooperation in Evolving Networks.

The sustainability of biological, social, economic and ecological communities is often determined by the outcome of social conflicts between cooperative and selfish individuals (cheaters). Cheaters avoid the cost of contributing to the community and can occasionally spread in the population leading to the complete collapse of cooperation. Although such collapse often unfolds unexpectedly, it is unclear whether one can detect the risk of cheater’s invasions and loss of cooperation in an evolving community. Here, we combine dynamical networks and evolutionary game theory to study the abrupt loss of cooperation with tools for studying critical transitions. We estimate the risk of cooperation collapse following the introduction of a single cheater under gradually changing conditions. We observe an increase in the average time it takes for cheaters to be eliminated from the community as the risk of collapse increases. We argue that such slow system response resembles slowing down in recovery rates prior to a critical transition. In addition, we show how changes in community structure reflect the risk of cooperation collapse. We find that these changes strongly depend on the mechanism that governs how cheaters evolve in the community. Our results highlight novel directions for detecting abrupt transitions in evolving networks.

Game theoretic simulation on the mimicry honeypot

A mimicry honeypot framework based on game theory is presented in our work, which can calculate the equilibrium strategy of the deceptive game using non-cooperative incomplete dynamic game theory, and make decisions for the mimicry framework to deploy the simple service, the honeypot and the fake honeypot. A mimicry prototype is implemented using NS2 platform, and simulation experiments are launched to validate the decision-making result and the deceptive performance of the mimicry honeypot. The empirical study shows that the mimicry honeypot framework based on game theory can be able to influence the equilibrium strategy results by dynamically changing the deployment vector of the mimicry system. It validates that the mimicry honeypot framework has better flexibility, activeness and fraudulence than the traditional honeypot.

Research on the Governance Mechanism of Aviation Complex Product Manufacturing Supply Chain Based on Dynamic Game Theory

In the manufacturing process of aeronautical complex products, for the following problems: develop long production cycle, a large number of ancillary products, a plurality of participating units, etc, and the status of the frequency of quality problems, using single-phase static game model in the case of asymmetric information, study on Supplier Quality insufficient investment, which resulting in opportunistic behaviour reasons. And using KMRW dynamic game model, we quantitative analysis the mechanism and crucial role of reputation mechanisms to ensure aeronautical complex product manufacturing supply chain and effective operation.

Study on the Cumulative Innovation Effect of the Competitive Patent Pools Based on the Different Technical Standards

Multi-patent pools based on different technical standards are appearing in many technique industries with competitions becoming intensive among technical standards. Theoretical model of cumulative innovation effect of competitive patent pools based on different technical standards is developed by dynamic game theory in this paper to study the cumulative innovation effect of competitive patent pool under the different patent types of relationship between patents, which are blocking patent, substitutability patent and additional innovation patent. This research indicates: the R&D investments of an enterprise inside a patent pool increase (or decrease) as the R&D investments of other enterprises inside the same patent pool decrease (or increase) or as the R&D investments of the enterprises inside another patent pool or the R&D investments of the enterprises outside patent pools increase (or decrease) during the patent race of blocking patent. The bigger differentiation degree between patents is, the R&D investments of all enterprises are more during the patent race of substitutability patent. The R&D investments of an enterprise inside a patent pool are bigger than outside the patent pools during the patent race of additional innovation patent.

城市存量土地再开发理论模型构建—基于动态博弈视角

城市土地再开发对提高城镇土地集约节约利用水平具有重要意义。通过对土地收储模式和自行开发模式的流程结构、权利、利益与风险演化的量化分析，构建了基于动态博弈视角的城市存量土地再开发理论模型。结论如下：1) 在规划信息不确定条件下，博弈模型将会形成两个纳什均衡；2) 从“占劣策略”角度，只要在“招拍挂”政策下交易成本够高，就会使均衡行动变成“严格占劣”的策略，使地方政府完全采用自主开发政策；3) 存量土地的增值收益分成比例也是重要因素，若分配比例过小，会使得均衡行动变为“严格占劣”的策略，使地方政府完全没有激励采用自主开发政策；4) 最终模型的均衡结果和最优存量土地开发模式依赖于相关单位价格变量与决策参数之间的互动变化。 Urban land re-development is of great significance to improve the level of urban land intensive utilization. Based on the quantitative analysis of land reserve mode and self development mode of land process structure, rights, interests and evolution of risk, a theoretical model of urban land re-development based on dynamic game theory was constructed. Conclusions are as follows: 1) Under the uncertainty of the planning information, the game model will form two Nash equilibrium; 2) From dominated strategy perspective, as long as the policy transaction costs are high enough, a strictly dominated strategy would be made; local governments would adopt the policy of independent development; 3) Revenue sharing ratio of stock land is also an important factor. If the ratio is too small, a strictly dominated strategy would also be made; the local government has no incentive to adopt the policy of independent development; 4) The equilibrium results of the final model and the optimal stock land development model depend on the interaction between the unit price and the decision parameters.

A Dynamic Evolutionary Game Model of Modular Production Network

As a new organization mode of production in the 21st century, modular production network is deemed extensively to be a source of competitiveness for lead firms in manufacturing industries. However, despite the abundant studies on the modular production network, there are very few studies from a dynamic perspective to discuss the conditions on which a modular production network develops. Based on the dynamic evolutionary game theory, this paper constructs a model, which incorporates several main factors influencing the development of modular production network. By calculating the replicator dynamics equations and analyzing the evolutionary stable strategies, this paper discusses the evolution process of cooperation strategies of member enterprises in a modular production network. Furthermore, by using NetLogo software to simulate the model, this paper verifies the effectiveness of the model. From the model, we can find that the final stable equilibrium strategy is related to such factors as the initial cost, the extra payoff, the cooperation willingness of both parties, the cooperation efforts, and the proportion each party can get from the extra payoff. To encourage the cooperation of production integrator and modular supplier, some suggestions are also provided.

Using Cognitive Radio for Interference-Resistant Industrial Wireless Sensor Networks: An Overview

Industrial wireless sensor networks (IWSNs) have to contend with environments that are usually harsh and time-varying. Industrial wireless technology, such as WirelessHART and ISA 100.11a, also operates in a frequency spectrum utilized by many other wireless technologies. With wireless applications rapidly growing, it is possible that multiple heterogeneous wireless systems would need to operate in overlapping spatiotemporal regions. Interference such as noise or other wireless devices affects connectivity and reduces communication link quality. This negatively affects reliability and latency, which are core requirements of industrial communication. Building wireless networks that are resistant to noise in industrial environments and coexisting with competing wireless devices in an increasingly crowded frequency spectrum is challenging. To meet these challenges, we need to consider the benefits that approaches finding success in other application areas can offer industrial communication. Cognitive radio (CR) methods offer a potential solution to improve resistance of IWSNs to interference. Integrating CR principles into the lower layers of IWSNs can enable devices to detect and avoid interference, and potentially opens the possibility of utilizing free radio spectrum for additional communication channels. This improves resistance to noise and increases redundancy in terms of channels per network node or adding additional nodes. In this paper, we summarize CR methods relevant to industrial applications, covering CR architecture, spectrum access and interference management, spectrum sensing, dynamic spectrum access (DSA), game theory, and CR network (CRN) security.

Competition vs. collaboration in the generation and adoption of a sequence of new technologies: a game theory approach

ABSTRACTThe study provides a game theoretic exploration of firms’ decisions on whether to compete or collaborate in the generation and adoption of a sequence of new technologies. Different from models proposed by previous studies, which concentrates on process innovation and a two-strategy set (innovation or do nothing), the present game theory model emphasises product innovation and a three-strategy set (innovation, collaboration, or do nothing). The study makes three contributions. The proposed game theory model extends current understanding of the impacts of collaboration possibilities and collaboration cost in a dynamic game theory. Further, the model clarifies the impact of transaction costs on the outcome. Finally, the study finds that the relationship between collaboration costs is not univariate, but depends on the market type and various market characteristics, such as technology gap, technology level, the product substitution index, transaction costs, and the discount rate of price sensitiveness.

Book Review: Mathematical Game Theory and Applications Vladimir Mazalov, Wiley 2014

The book, written by Vladimir Mazalov, gives a fascinating view on the state-ofthe-art of a classical and modern Game Theory. It addresses a wide variety of game types (from matrix games to differential games with all conceivable stopovers), providing a great collection of examples (from economics to sport). The examples are not only illustrative but in many cases reflect the research results of the author (optimal stopping games, arbitration games, bioresource sharing models, fish wars, location problem, poker model, etc.) All the examples, presented in the book, are thoroughly elaborated, beginning with a rather simple, understandable, model, and gradually becoming more complicated. This also features a pedagogical value of the book: a reader, not so familiar with the mathematical game theory, an undergraduate student, for example, can use it as a helpful textbook, guiding her/him from the basics of the theory to its various complex applications. Numerous examples produce for a reader a “stable bridge” between mathematics and a real life of individuals and groups. The author emphasizes this close connection by animating the mathematical objects: sets in this book “enjoy” convexity, functions “suffer” from being discontinuous, and so on. The book consists of 10 chapters. First seven chapters are devoted to the noncooperative games: Chapters 1–3 deal with the normal-form games, while Chapters 4–7 address the extensive-form (positional) games. The essentials of the cooperative games are given in Chapter 8. In Chapter 9, the author discusses the network games. The last but not the least, Chapter 10 contains the theory of dynamic (discrete-time and differential) games. Each chapter is equipped by the set of the exercises. Chapter 1 deals with a normal-form two-players game, where the players choose their strategies from prescribed sets in the beginning of the game and their payoffs functions are given. Fundamental theorems on the existence of Nash equilibrium in

Game Analysis of Driving Behavior in Mixed Traffic

AbstractA utility function of driving behavior for non-motor and motor vehicles is built based on dynamic reduplicate game theory to study the decision-making behavior of a driver for non-motor and motor vehicles in a mixed-traffic environment. This utility is built according to a driver’s personality that affects decision-making behavior, time refinement, and time difference to a conflict point between non-motor vehicles and motor vehicles in each period. Analysis of the utility function of driving behavior for non-motor and motor vehicles shows that, a Nash equilibrium exists in the game process, and the optimal decision making, for non-motor and motor vehicles in a dynamic game is obtained. The illustration shows that, during decision-making, (1) impulsive drivers choose the acceleration strategy; (2) mild drivers prefer the uniform or deceleration strategy; and (3) cautious drivers choose the deceleration strategy.

Coordinating contracts for a three-lever logistics service supply chain

A three-lever logistics service supply chain (LSSC) consisting of a logistics service integrator (LSI), a logistics service provider (LSP), and a functional logistics service subcontractor (LSS) is discussed in this paper. Since the improvement of logistics service levels caused by the efforts of LSS can significantly affect the market demand for LSSC, a dynamic game theory model is developed to solve the coordinating contract design problem in this condition. A joint contract which combined with the option contract and the cost-sharing and revenue-sharing contract is designed. The option contract is between LSI and LSP, which are regarded as a whole to share revenue and cost with LSS in the two transactions of LSSC. The reasonable choice of parameters can attain the maximum of the expected profit of LSSC and the win-win good among all members. Finally, a corresponding numerical example is presented to illustrate the conclusions.

A predator-prey particle swarm optimization approach to multiple UCAV air combat modeled by dynamic game theory

Dynamic game theory has received considerable attention as a promising technique for formulating control actions for agents in an extended complex enterprise that involves an adversary. At each decision making step, each side seeks the best scheme with the purpose of maximizing its own objective function. In this paper, a game theoretic approach based on predatorprey particle swarm optimization (PP-PSO) is presented, and the dynamic task assignment problem for multiple unmanned combat aerial vehicles (UCAVs) in military operation is decomposed and modeled as a two-player game at each decision stage. The optimal assignment scheme of each stage is regarded as a mixed Nash equilibrium, which can be solved by using the PP-PSO. The effectiveness of our proposed methodology is verified by a typical example of an air military operation that involves two opposing forces: the attacking force Red and the defense force Blue.