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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 ...
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Remora Optimization Algorithm Step-by-Step Learning with Example ~xRay Pixy

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Remora Optimization Algorithm (ROA)


Remora Optimization Algorithm (ROA) is recently proposed Bionics based, Nature Inspired Metaheuristic Optimization Algorithm used to solve Global Optimization Problems. Remora Optimization Algorithm is proposed by Heming Jia, Xiaoxu Peng and Chunbo Lang in 2021. Remora Optimization Algorithm is basically inspired by the Parasitic features of remora and Random Host Replacement of remora. Remora use suction technique for their survival. They attached themselves to the host animals such as Whales, Sea Turtles, Sharks, Swordfish and other. They use their suction disk to easily attach themselves with host.

Remora clean host body from Parasites, Bacteria's, and in return they get their food for survival. They also eat the leftover food from their host. In ROA, Whale Optimization Algorithm and Swordfish Optimization Algorithm is used to update remora position in the search space. In ROA, the fusion framework is used by switching between Remora and two host (Whale, Swordfish). Remora follow 2 host Whale and Swordfish in this algorithm.
Remora Optimization Algorithm Advantages:
  • Solve Global Optimization Problems.
  • Better as compare to heuristic algorithms.
Remora Optimization Algorithm Limitations:
  • Slow Convergence Rate.
  • Poor Solution Accuracy.
  • For some engineering problems stuck in local optima.
Remora Optimization Algorithm Steps:
  • Initialize population for N remora.
  • Using fitness function evaluate performance for each remora.
  • Find out the best and worst remora in the current population.
  • Update algorithm parameters.
  • Update Remora Position
  • Again evaluate performance for updated remoras.
  • Compare solution and display best among all.
  • Find out the best and worst remora in the current population.
  • Update algorithm parameters.
  • Update Remora Position.
  • Again evaluate performance for updated remoras.
  • Compare solution and display best among all.


Meta-heuristic Algorithms   CLICK HERE...

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