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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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Pareto Optimal Solutions || Multi Objective Optimization Problems || ~xR...

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Learn how to calculate Pareto optimal solutions. Video Chapters: Pareto Optimality 00:00 Introduction 00:24 Pareto Optimality 02:33 Pareto Optimality Importance 03:29 Pareto Optimality Disadvantages 03:54 Pareto Optimality Applications 04:02 Example 1 Robot in Field 05:39 Steps to Calculate Pareto Optimality 07:41 Example 2 Math Example 11:03 Example 3 Resource Allocation Problem 16:09 Conclusion
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Robots Using PSO || Multi-Objective Optimization || ~xRay Pixy

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Learn Multi-Objective Optimization:  PSO Example for Robots with Different Battery Levels Video Chapters: Robotics and PSO 00:00 Introduction 00:36 Robots Finding the Optimal Path 05:45 Multi-Objective Optimization 06:44 Objectives 08:46 Flowchart 09:08 Results 11:15 Conclusion
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BAT ALGORITHM || PYTHON CODE || ~xRay Pixy

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Learn Bat Algorithm Implementation in Python. Video Chapters: Bat Algorithm 00:00 Introduction 00:42 Bat Algorithm Key Concepts 01:58 Bat Algorithm Pseudocode 02:35 Objective Function 02:49 Parameters 03:09 Python Code 06:30 BA Main Loop Start 12:30 Result The Bat Algorithm is a nature-inspired optimization algorithm developed by Xin-She Yang in 2010. It is based on the echolocation behavior of bats. Bats use echolocation to detect prey, avoid obstacles, and navigate in the dark. The algorithm simulates this behavior to find optimal solutions in complex optimization problems. Applications: The Bat Algorithm has been used in various fields, including engineering design, image processing, data mining, and robotics, for solving complex optimization problems. PYTHON CODE: import numpy as np # Define the objective function  def objective_function(x):     return np.sum(x**2) # Initialize the bat population def initialize_bats(n_bats, dim, lower_bound, upper_bound, f_min, f_m...
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Deep Learning in Robotics || Smart Robotics || ~xRay Pixy

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Learn the role of deep learning in robotics. Video Chapters: Smart Robots 00:00 Introduction 00:42 Why Optimization? 03:47 Deep Learning  04:28 Role of Deep Learning in Robotics 07:03 How Deep Learning Applied in Robotics 09:58 Example Mobile Robot 14:33 Conclusion
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Marine Robotics and Metaheuristics || Deep Exploration || ~xRay Pixy

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Learn the role of Metaheuristics in Advanced Solutions in Marine Robotics. Video Chapters: Marine Robotics 00:00 Introduction 00:25 Marine Robots 02:11 Marine Robotics Applications   04:14 Marine Robotics Technologies 05:46 Marine Robotics Challenges 06:21 Marine Robotics Algorithms 10:30 Metaheuristic Algorithms in Marine Robotic 13:09 Conclusion 
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