How to Conquer the World

Overview

Discover the art of mastering the board game Risk with this engaging YouTube event. Dive into developing a genetic algorithm using Python, a powerful tool for optimizing your strategies.

Uncover the secrets of object-oriented design and AI techniques that can help simulate and optimize your gameplay.

Whether you're an AI enthusiast or a gaming strategist, this event is tailored for those eager to enhance their skills and conquer the world of Risk. Join us and learn from the comfort of your home, leveraging the expertise shared in this online conference.

Syllabus

• Introduction to the Course
Overview of Course Objectives
Introduction to the Game of Risk
Basic Concepts in AI and Genetic Algorithms
Prerequisites and Tools Setup
• Understanding the Board Game Risk
Game Rules and Strategies
Exploring the Game Mechanics
Identifying Key Challenges and Objectives in Risk
• Python Programming Refresher
Basic Syntax and Data Structures
Functions and Modules
Introduction to Object-Oriented Programming (OOP)
• Object-Oriented Design for Risk Simulation
Modeling the Game Components
Designing Classes for Players, Armies, and Territories
Implementing Interaction Rules and Game Flow
• Fundamentals of Genetic Algorithms
Introduction to Evolutionary Algorithms
Key Concepts: Population, Chromosomes, Fitness Functions
Genetic Operators: Selection, Crossover, Mutation
• Developing a Genetic Algorithm for Risk
Setting Up the Problem and Encoding the Strategies
Designing and Implementing a Fitness Function
Applying Genetic Operators to Evolve Solutions
• Game Simulation and Optimization
Running Simulations for Strategy Testing
Analyzing Results and Debugging Strategies
Tuning Parameters for Optimal Performance
• Advanced AI Strategies in Gaming
Heuristics and Strategy Development
Hybrid Approaches: Combining AI Techniques
Machine Learning for Adaptive Gameplay
• Practical Applications and Project Work
Designing and Building an AI-Powered Risk Bot
Applying Learned Techniques to Variants and Other Games
Case Studies of Successful AI in Gaming
• Course Completion and Next Steps
Reviewing Key Learnings and Concepts
Final Project Presentation and Feedback
Further Reading and Resources for Continued Learning

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Subjects

Conference Talks