Basics of qualitative research: Grounded theory procedures and techniques

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

Introduction to stochastic programming

Power Aware Routing in Mobile Ad Hoc Networks

The Grid 2: Blueprint for a New Computing Infrastructure

The 3D bin packing problem 3DBPP is a practical problem modeled from modern industry application such as container ship loading and plane cargo management. Unlike traditional bin packing problem where all bins are of the same size, this paper investigates a more general type of 3DBPP with bins of various sizes. We proposed a modified univariate marginal distribution algorithm UMDA for solving the problem. A packing strategy derived from a deepest bottom left packing method was employed. The modified UMDA was experimentally compared with CPLEX and a genetic algorithm GA approach. The experimental study showed that the proposed algorithm performed better than GA and CPLEX for large-scale instances.

An Estimation of Distribution Algorithm for the 3D Bin Packing Problem with Various Bin Sizes

We consider the problem of scheduling a set of simultaneousl y available jobs on a single machine. The objective is to determine a schedule that minimizes the class-based completion time variance (CB-CTV) of the jobs while reducing the overall CTV is taken as the secondary objective. This non-regular performance measure is closely related to service stability and of practical significance in many areas. We prove that a CB-CTV problem can be transformed into a series of CTV minimization problems, which allows us to apply the existing well developed properties and scheduling methods of CTV. Computational results are presented to show the trade-off between the overall CTV and CB-CTV and indicate that it is desirable to minimize CB-CTV with regard to service stability and consistency from customers' point of view. Keywords ─Completion time variance (CTV), Class-based completion time variance (CB-CTV), Job scheduling, Optimization

http://www.orstw.org.tw/IJOR/vol4no1/Paper-2--IJOR-vol4_1_-Xueping%20Li.pdf

Minimizing Class-based Completion Time Variance on a Single Machine

Analyzing Trade-offs Between Efficiency and Equity on Public Facility Location

Makespan Minimization on Identical Parallel Machines with Precedence Constraints

It has been 20 years since the National Academy of Medicine released its report, "To Err Is Human," which shocked the healthcare community on the pervasiveness of medical error. While errors in medication administration are a significant contributor to medical error, research seeking to understand the complex systems nature and occurrence of medication administration error is limited. Computer modeling is increasingly being used in the healthcare industry to assess the impact of changes made to healthcare processes. The objective of the study is to evaluate the use of agent-based modeling, a type of computer modeling that allows the simulation of virtual individuals and their behavior, to simulate nurse performance in the medication administration process. The model explores the effect of Just-in-Time information, as an intervention, on the occurrence of medication error. The model demonstrated significant utility in understanding the interplay of the system elements of the nurse medication administration process. Therefore this approach, using systems-level computer simulation such as agent-based models, can help administrators understand the effects of changes to the medication administration process as they work to reduce errors and increase performance.

Xueping Li

Papers

An Estimation of Distribution Algorithm for the 3D Bin Packing Problem with Various Bin Sizes

Minimizing Class-based Completion Time Variance on a Single Machine

Analyzing Trade-offs Between Efficiency and Equity on Public Facility Location

Makespan Minimization on Identical Parallel Machines with Precedence Constraints

Agent-Based Modeling Simulation of Nurse Medication Administration Errors.