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Table Of Integrals Series And Products

Preface 1. Decision-Theoretic Foundations 1.1 Game Theory, Rationality, and Intelligence 1.2 Basic Concepts of Decision Theory 1.3 Axioms 1.4 The Expected-Utility Maximization Theorem 1.5 Equivalent Representations 1.6 Bayesian Conditional-Probability Systems 1.7 Limitations of the Bayesian Model 1.8 Domination 1.9 Proofs of the Domination Theorems Exercises 2. Basic Models 2.1 Games in Extensive Form 2.2 Strategic Form and the Normal Representation 2.3 Equivalence of Strategic-Form Games 2.4 Reduced Normal Representations 2.5 Elimination of Dominated Strategies 2.6 Multiagent Representations 2.7 Common Knowledge 2.8 Bayesian Games 2.9 Modeling Games with Incomplete Information Exercises 3. Equilibria of Strategic-Form Games 3.1 Domination and Ratonalizability 3.2 Nash Equilibrium 3.3 Computing Nash Equilibria 3.4 Significance of Nash Equilibria 3.5 The Focal-Point Effect 3.6 The Decision-Analytic Approach to Games 3.7 Evolution. Resistance. and Risk Dominance 3.8 Two-Person Zero-Sum Games 3.9 Bayesian Equilibria 3.10 Purification of Randomized Strategies in Equilibria 3.11 Auctions 3.12 Proof of Existence of Equilibrium 3.13 Infinite Strategy Sets Exercises 4. Sequential Equilibria of Extensive-Form Games 4.1 Mixed Strategies and Behavioral Strategies 4.2 Equilibria in Behavioral Strategies 4.3 Sequential Rationality at Information States with Positive Probability 4.4 Consistent Beliefs and Sequential Rationality at All Information States 4.5 Computing Sequential Equilibria 4.6 Subgame-Perfect Equilibria 4.7 Games with Perfect Information 4.8 Adding Chance Events with Small Probability 4.9 Forward Induction 4.10 Voting and Binary Agendas 4.11 Technical Proofs Exercises 5. Refinements of Equilibrium in Strategic Form 5.1 Introduction 5.2 Perfect Equilibria 5.3 Existence of Perfect and Sequential Equilibria 5.4 Proper Equilibria 5.5 Persistent Equilibria 5.6 Stable Sets 01 Equilibria 5.7 Generic Properties 5.8 Conclusions Exercises 6. Games with Communication 6.1 Contracts and Correlated Strategies 6.2 Correlated Equilibria 6.3 Bayesian Games with Communication 6.4 Bayesian Collective-Choice Problems and Bayesian Bargaining Problems 6.5 Trading Problems with Linear Utility 6.6 General Participation Constraints for Bayesian Games with Contracts 6.7 Sender-Receiver Games 6.8 Acceptable and Predominant Correlated Equilibria 6.9 Communication in Extensive-Form and Multistage Games Exercises Bibliographic Note 7. Repeated Games 7.1 The Repeated Prisoners Dilemma 7.2 A General Model of Repeated Garnet 7.3 Stationary Equilibria of Repeated Games with Complete State Information and Discounting 7.4 Repeated Games with Standard Information: Examples 7.5 General Feasibility Theorems for Standard Repeated Games 7.6 Finitely Repeated Games and the Role of Initial Doubt 7.7 Imperfect Observability of Moves 7.8 Repeated Wines in Large Decentralized Groups 7.9 Repeated Games with Incomplete Information 7.10 Continuous Time 7.11 Evolutionary Simulation of Repeated Games Exercises 8. Bargaining and Cooperation in Two-Person Games 8.1 Noncooperative Foundations of Cooperative Game Theory 8.2 Two-Person Bargaining Problems and the Nash Bargaining Solution 8.3 Interpersonal Comparisons of Weighted Utility 8.4 Transferable Utility 8.5 Rational Threats 8.6 Other Bargaining Solutions 8.7 An Alternating-Offer Bargaining Game 8.8 An Alternating-Offer Game with Incomplete Information 8.9 A Discrete Alternating-Offer Game 8.10 Renegotiation Exercises 9. Coalitions in Cooperative Games 9.1 Introduction to Coalitional Analysis 9.2 Characteristic Functions with Transferable Utility 9.3 The Core 9.4 The Shapkey Value 9.5 Values with Cooperation Structures 9.6 Other Solution Concepts 9.7 Colational Games with Nontransferable Utility 9.8 Cores without Transferable Utility 9.9 Values without Transferable Utility Exercises Bibliographic Note 10. Cooperation under Uncertainty 10.1 Introduction 10.2 Concepts of Efficiency 10.3 An Example 10.4 Ex Post Inefficiency and Subsequent Oilers 10.5 Computing Incentive-Efficient Mechanisms 10.6 Inscrutability and Durability 10.7 Mechanism Selection by an Informed Principal 10.8 Neutral Bargaining Solutions 10.9 Dynamic Matching Processes with Incomplete Information Exercises Bibliography Index

博弈论 : 矛盾冲突分析 = Game theory : analysis of conflict

The author's preface gives an outline: "This book is about weakconvergence methods in metric spaces, with applications sufficient to show their power and utility. The Introduction motivates the definitions and indicates how the theory will yield solutions to problems arising outside it. Chapter 1 sets out the basic general theorems, which are then specialized in Chapter 2 to the space C[0, l ] of continuous functions on the unit interval and in Chapter 3 to the space D [0, 1 ] of functions with discontinuities of the first kind. The results of the first three chapters are used in Chapter 4 to derive a variety of limit theorems for dependent sequences of random variables. " The book develops and expands on Donsker's 1951 and 1952 papers on the invariance principle and empirical distributions. The basic random variables remain real-valued although, of course, measures on C[0, l ] and D[0, l ] are vitally used. Within this framework, there are various possibilities for a different and apparently better treatment of the material. More of the general theory of weak convergence of probabilities on separable metric spaces would be useful. Metrizability of the convergence is not brought up until late in the Appendix. The close relation of the Prokhorov metric and a metric for convergence in probability is (hence) not mentioned (see V. Strassen, Ann. Math. Statist. 36 (1965), 423-439; the reviewer, ibid. 39 (1968), 1563-1572). This relation would illuminate and organize such results as Theorems 4.1, 4.2 and 4.4 which give isolated, ad hoc connections between weak convergence of measures and nearness in probability. In the middle of p. 16, it should be noted that C*(S) consists of signed measures which need only be finitely additive if 5 is not compact. On p. 239, where the author twice speaks of separable subsets having nonmeasurable cardinal, he means "discrete" rather than "separable." Theorem 1.4 is Ulam's theorem that a Borel probability on a complete separable metric space is tight. Theorem 1 of Appendix 3 weakens completeness to topological completeness. After mentioning that probabilities on the rationals are tight, the author says it is an

Convergence of probability measures

Matrix Factorization Techniques for Recommender Systems

/pdf/a-break-in-the-clouds-towards-a-cloud-definition-svovsw1r5a.pdf

A Break in the Clouds: Towards a Cloud Definition

Power Optimization for Maximum Channel Capacity in MIMO Relay System

In software-defined networking (SDN), the communication between controllers and switches is very important, for switch can only work by relying on flow tables received from its controller. Therefore, how to ensure the reliability of the communication between controllers and switches is a key problem in SDN. In this paper, we study this problem from two aspects: the controller placement and the resource backup aspect. Firstly, in order to implement the reliable communication and meet the required propagation delay between controllers and switches, a min-cover based controller placement approach is proposed. Then, in order to protect both controllers and control paths from regional failure, a backup method based on an exponential decay failure model is proposed, which considers the regional influence and the survivability of backup controllers and control paths. Simulations show that our controller placement approach can meet the reliability and delay requirement with appropriate controller allocation scheme, and our backup method can improve the survivability of backup controllers and control paths while ensuring the performance of control network.

Resource Allocation for Reliable Communication Between Controllers and Switches in SDN

Multiple input and multiple output (MIMO) can greatly enhance the performance of wireless system. However, the limited battery life and terminal size of the user equipment (UE) in a cellular system put a constraint on the performance enhancement by MIMO. Especially when the transmitter has more antenna than the receiver in downlink, the conventional MIMO schemes can only exploit partial multiplexing gain and diversity gain. For a multiuser system, multiuser diversity gain can be achieved by exploiting the independent frequency and spatial selective fading one another. In this paper, different multiuser multiple access schemes with greedy scheduling of MIMO OFDMA are investigated, e.g. TDMA, FDMA/TDMA and SDMA/FDMA/TDMA. For full spatial-frequency multiuser diversity gain and spatial multiplexing gain can be achieved, SDMA/FDMA/TDMA obtains highest spectrum efficiency. Its gain exceeds that of TDMA and FDMA/TDMA at least 80% and 40% respectively. The more antennas configured, the more gain can be observed from SDMA/FDMA/TDMA

Multiple Access of MIMO OFDMA: TDMA, FDMA/TDMA, or SDMA/FDMA/TDMA

The construction of energy-efficient network and achievement of green communication have garnered great attention as a promising a way to reduce network operating costs and C emissions. Moreover, recently the deadline-aware and energy-efficient routing and scheduling algorithms in data center network have been attracting a broad attention. However, the dynamic scheduling for flows has not been explicitly studied by the existing research. In this paper, we investigated the dynamic flow scheduling in data center network, and propose a deadline-aware and energy-efficient dynamic flow scheduling (DEDFS) algorithm, assuming the path of the flow could be calculated in advance and pre-stored. In addition, the number of mouse flows in data center network accounts for main proportion, but consumption is very small. In order to achieve the balance of energy-saved and efficiency, mouse flows will be directly transferred, while elephant flows will be scheduled by the Most-Critical-First static strategy based dynamic scheduling algorithm. It selects the interval of largest energy consumption density as the critical interval, and all of the flows in this critical interval will be preferentially scheduled. Finally, the feasibility and validity of the algorithm are verified by simulation.

Deadline-aware and energy-efficient dynamic flow scheduling in data center network

This paper studies a spectrum sharing cognitive radio (CR) network coexisting with a primary network. In particular, the channel state information (CSI) between the secondary transmitter (STx) and the primary receiver (PRx) is assumed to be outdated due to channel feedback latency. We assume that the secondary user (SU) shall satisfy a given delay quality-of-service (QoS) constraint as well as the average interference power constraint. Our aim is to obtain the maximum arrival rate of the SU under aforementioned constraints with the outdated CSI. In this respect, we derive the optimal power allocation scheme to achieve the maximum effective capacity, and further derive the effective capacity. The closed-form expressions for the lower and upper bounds on the effective capacity are also provided. Numerical and simulation results are presented to show the effects of the outdated CSI. It is shown that the effective capacity of the SU is insensitive to the channel correlation coefficient especially under low channel correlation coefficient.

Ying Wang

Papers

Power Optimization for Maximum Channel Capacity in MIMO Relay System

Resource Allocation for Reliable Communication Between Controllers and Switches in SDN

Multiple Access of MIMO OFDMA: TDMA, FDMA/TDMA, or SDMA/FDMA/TDMA

Deadline-aware and energy-efficient dynamic flow scheduling in data center network

Capacity of cognitive radio under delay quality-of-service constraints with outdated channel feedback