Unlock the Power of Game Theory in AI!Discover the revolutionary approach to artificial intelligence with "Algorithm Recipes Based On Game Theory: For AI Models". Written by renowned AI expert Richard Aragon, this book delves into the fascinating intersection of game theory and AI, offering a collection of innovative algorithms designed to solve complex problems.Why You Should Read This Book• Innovative Approach: Explore how principles from game theory can inspire and enhance AI algorithms, leading to more robust, fair, and efficient solutions.• Comprehensive Coverage: Each chapter presents a unique "recipe" with a use case, mathematical foundation, ingredients, preparation instructions, deployment advice, code implementation, and a summary of the algorithm’s novelty and usability.• Practical Applications: Learn how to apply these cutting-edge algorithms to real-world problems, including multi-agent systems, feature selection, optimization, anomaly detection, and more.• Expert Insights: Benefit from Richard Aragon's deep expertise and practical experience in AI and game theory.Inside the Book• Chapter 1: The Nash Equilibrium Optimizer (NEO)• Chapter 2: The Minimax Classifier (MMC)• Chapter 3: The Cooperative Multi-Agent Reinforcement Learner (CMARL)• Chapter 4: The Shapley Value Feature Selector (SVFS)• Chapter 5: The Stackelberg Game Recommender System (SGRS)• Chapter 6: The Evolutionary Stable Strategy Neural Network (ESSNN)• Chapter 7: The Zero-Sum Game Neural Network Trainer (ZSGNNT)• Chapter 8: The Pareto Optimal Multi-Objective Optimizer (POMOO)• Chapter 9: The Bayesian Game Anomaly Detector (BGAD)• Chapter 10: The Cournot Competition Regression Model (CCRM)• Chapter 11: The Evolutionary Game Theory-Based Genetic Algorithm (EGTGA)• Chapter 12: The Cooperative Markov Decision Process (CMDP)• Chapter 13: The Mixed Strategy Nash Equilibrium Optimizer (MSNEO)• Chapter 14: The Cooperative Bargaining Agreement Clustering (CBAC)• Chapter…