tailieunhanh - Computational Learning Theory

Several fields in computer science and economics are focused on the analysis of Game theory. Usually they observe Game Theory as a way to solve optimization problems in systems where the participants act independently and their decisions affect the whole system. Following is a list of research fields that utilize Game Theory | Computational Learning Theory Spring Semester 2003 4 Lecture 1 March 2 Lecturer Yishay Mansour Scribe Gur Yaari Idan Szpektor Introduction Several fields in computer science and economics are focused on the analysis of Game theory. Usually they observe Game Theory as a way to solve optimization problems in systems where the participants act independently and their decisions affect the whole system. Following is a list of research fields that utilize Game Theory Artificial Intelligence AI - Multiple Agents settings where the problem is usually a cooperation problem rather than a competition problem. Communication Networks - Distribution of work where each agent works indepen-dantly. Computer Science Theory - There are several subfields that use Game Theory Maximizing profit in bidding Minimum penalty when using distributional environment Complexity Behavior of large systems Course Syllabus Basic definitions in Game Theory concentrating on Nash Equilibrium Coordination Ratio Comparison between global optimum and Nash Equilibrium Load Balancing Models Computation of Nash Equilibrium Zero Sum games Linear Programming Existence of Nash Equilibrium in general games 1 2 Lecture 1 March 2 Regret - playing an unknown game. Optimizing a player s moves when the player can only view her own payoff Vector Payoff - the Payoff function is a vector and the target is to reach a specific target set Congestion and Potential games - games that model a state of load Convergence into Equilibrium Other. Strategic Games A strategic game is a model for decision making where there are N players each one choosing an action. A player s action is chosen just once and cannot be changed afterwards. Each player i can choose an action ai from a set of actions Aị. let A be the set of all possible action vectors XjeNAj. Thus the outcome of the game is an action vector a E A. All the possible outcomes of the game are known to all the players and each player i has a preference relation .

• Toán học
• Pareto Optimal
• Nash Equilibrium
• Matrix Representation
• Strategic Game
• Battle of the Sexes
• Interactive EMO
• Multi objective optimization
• Pareto optimal solutions
• Pareto optimal set
• Multi point Interactive method
• steady state
• fully funded system
• Overlapping Generations Model
• Pareto efficient
• Pension System
• BMC Bioinformatics
• Optimal control
• Dynamic modeling
• Multi criteria optimization
• Pareto optimality
• Gradient descent directions
• Improvement directions
• Multi objective evolutionary algorithms
• Evolution algorithms
• Constructive algorithm to maximize the useful life
• Mechanical system subjected to ageing
• Non resuppliable spares parts
• Generalized poisson process
• Pareto optimal frontier
• Useful life maximisation
• Optimizing turning process
• Genetic algorithm
• Optimization solution