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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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What are the best algorithms for face detection in Matlab?

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The best algorithms for face detection in Matlab = Viola-Jones Algorithm
Face from the different digital images can be detected. The vision. CascadeObjectDetector uses the Viola-Jones algorithm to detect people’s Faces, Noses, Eyes, Mouth or upper body. The Cascade Object Detector build into MATLAB to detect the facial features from a digital image.
  • Detects the left and right eyes separately.
  • Detects the mouth.
  • Detect the objects using the viola jones algorithm.
  • Detect a pair of eyes.
  • Detects faces that are upright and forward-facing.
For Face detection:
faceDetector=vision.CascadeObjectDetector('FrontalFaceCART');
For Eyes detection:
faceDetector=vision.CascadeObjectDetector('EyePairBig’);
I Created a Face Detection system using Viola- Jones algorithm.
Book : Face and Facial Expression Recognition
LINK : Face Doctor - Viola Jones
LINK
Project | Face Detection using Polar Harmonic Transforms ~xRay Pixy

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Cuckoo Search Algorithm for Optimization Problems

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PSO (Particle Swarm Optimization) Example Step-by-Step

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 Particle swarm optimization (PSO) What is meant by PSO? PSO is a computational method that Optimizes a problem. It is a Population-based stochastic search algorithm. PSO is inspired by the Social Behavior of Birds flocking. n Particle Swarm Optimization the solution of the problem is represented using Particles. [Flocking birds are replaced with particles for algorithm simplicity]. Objective Function is used for the performance evaluation for each particle / agent in the current population. PSO solved problems by having a Population (called Swarms) of Candidate Solutions (Particles). Local and global optimal solutions are used to update particle position in each iteration. How PSO will optimize? By Improving a Candidate Solution. How PSO Solve Problems? PSO solved problems by having a Population (called Swarms) of Candidate Solutions (Particles). The population of Candidate Solutions (i.e., Particles). What is Search Space in PSO? It is the range in which the algorithm computes th...
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how is the LBP |Local Binary Pattern| values calculated? Step-by-Step with Example

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PSO Python Code || Particle Swarm Optimization in Python || ~xRay Pixy

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There are about 1000 species of Bats. Bat Algorithm is based on the echolocation behavior of Micro Bats with varying pulse rates of emission and loudness. All bats use echolocation to sense distance and background barriers.  Microbats are small to medium-sized flying mammals. Micro Bats used a Sonar that is known as Echolocation to detect their prey. Bats fly randomly with the velocity at the position with a fixed frequency and loudness for prey.  Q. Whats is Frequency? A. Frequency is the number of waves that pass a fixed point in unit time. Wavelength is the minimum distance between two nearest particles which are in the same phase. Here, Sound waves are used by microbats to detect prey.  Q. What is Position? A. A place where something or someone is located.  Q. What is Velocity? A. Speed of something in a given direction.  Q. What is loudness. A. Loudness refers to how soft or loud sound seems to listeners.  Q. What is pulse rate? ...
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Grey Wolf Optimization Algorithm Numerical Example

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