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Nash Equilibrium In Game Theory ~xRay Pixy

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 Video Link  CLICK HERE... Learn Nash Equilibrium In Game Theory Step-By-Step Using Examples. Video Chapters: Nash Equilibrium  00:00 Introduction 00:19 Topics Covered 00:33 Nash Equilibrium  01:55 Example 1  02:30 Example 2 04:46 Game Core Elements 06:41 Types of Game Strategies 06:55  Prisoner’s Dilemma  07:17  Prisoner’s Dilemma Example 3 09:16 Dominated Strategy  10:56 Applications 11:34 Conclusion The Nash Equilibrium is a concept in game theory that describes a situation where no player can benefit by changing their strategy while the other players keep their strategies unchanged.  No player can increase their payoff by changing their choice alone while others keep theirs the same. Example : If Chrysler, Ford, and GM each choose their production levels so that no company can make more money by changing their choice, it’s a Nash Equilibrium Prisoner’s Dilemma : Two criminals are arrested and interrogated separately. Each has two ...

Soft Computing - Fuzzy Logic | Fuzzy Relations | DOM | FIS || Unit 1 || ...

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Learn Soft Computing Basics step-by-step using Example. Video Chapter: 00:00 Introduction 00:09 Topics Covered 02:13 What is Fuzzy Logic? 07:06 What is Crisp Set? 08:03 What is the Degree of Membership? 09:05 Fuzzy Logic Components 10:46 Fuzzy Logic Operators 11:47 Fuzzy Relations 15:03 Fuzzy Relation Composition 17:28 Fuzzy Inference System 17:52 Defuzzification What is a Crisp Set? A "crisp set" or "crisp logic" refers to the traditional, classical set theory and logic where elements either belong to a set or do not, with no in-between or degrees of membership. In crisp logic, membership is binary—something is either a member of a set (true) or not (false). What is a Fuzzy Logic? Fuzzy logic is a mathematical framework that deals with reasoning and decision-making in the presence of uncertainty and imprecision. Unlike classical (Boolean) logic, which is based on binary values (true or false, 0 or 1), fuzzy logic allows for the representation of parti...

Solving Transportation Problem ||Operations Research and Optimization|| ...

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Unit 1  - INTRODUCTION TO OPTIMIZATION ALGORITHMS Video Chapters: Optimization Techniques 00:00 Introduction 02:39 Optimization Statement 05:27 Constrained Optimization Problems 06:06 Constrained Optimization Methods 07:38 Transportation Problem 14:40 Unconstrained Optimization Problems 20:15 Conclusion 1. What is Optimization?      Optimization is the process of finding the best solution or set of solutions from a range of possible options, with the aim of maximizing or minimizing a particular objective function. The objective function is a mathematical expression that represents the quantity to be optimized, such as maximizing profit, minimizing cost, or achieving the highest performance. There are two main types of optimization problems: Maximization Problems: These involve finding the maximum value of an objective function. Examples : maximizing profit, revenue, efficiency, or any other desirable outcome. Minimization Problems: These involve ...
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