Algorithm Recipes Based On Game Theory For AI Models

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 15: The Shapley Value-Based Fair Feature Selection (SVFFS)
Who Should Read This Book:
* AI Researchers and Practitioners: Enhance your toolkit with game theory-inspired algorithms.
* Data Scientists: Discover innovative methods for model development and optimization.
* Students and Educators: Gain a comprehensive understanding of the intersection of game theory and AI.
* Developers: Access practical, ready-to-implement algorithms for real-world applications.
Why Choose This Book?
"Algorithm Recipes Based On Game Theory: For AI Models" is not just a book; it's a practical guide that bridges the gap between theoretical concepts and real-world applications. Whether you're an AI professional, a data scientist, or a student, this book provides the insights and tools needed to excel in the rapidly evolving field of artificial intelligence.



Algorithm Recipes Based On Game Theory For AI Models Fast Download
Algorithm Recipes Based On Game Theory For AI Models Full Download