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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 ...

Manta Ray Foraging Optimization (MRFO) Algorithm Step-by-Step Explanatio...

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Manta Ray Foraging Optimization (MRFO) Manta ray foraging optimization (MRFO) is a new optimization approach for global optimization problems. The Manta ray optimization algorithm is developed by Zhao et al. (2020). Manta ray optimization algorithm is a bio-inspired optimization technique. Manta ray optimization algorithm is inspired by foraging strategies of manta rays. Manta ray optimization algorithm is used to solve optimization problems. Manta Ray basic structure Manta Ray foraging is often found in groups. Three main manta Rays Foraging Strategies:  Chain Foraging Cyclone Foraging Somersault Foraging Chain Foraging: More than 50 Manta Rays line up. One behind another. (the line is formed by Manta Rays). Manta Rays observe plankton’s position and swim towards it. Manta Rays form a foraging chain by line-up from head to tail. Assumed that BEST Solution is plankton with high concentration manta rays want to approach. In every generation, all individuals will update their positi...
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