8 Hour Self-Paced Course or 1 Day Instructor-Led Training

8 Hour Self-Paced Course or 1 Day Instructor-Led Training

8 Hour Self-Paced Course or 1 Day Instructor-Led Training

AI+ Game Design Agent™

AI+ Game Design Agent™

AI+ Game Design Agent™

Design AI Agents that Power Next-Generation Game Development Workflows.

Design AI Agents that Power Next-Generation Game Development Workflows.

Design AI Agents that Power Next-Generation Game Development Workflows.

Get the AI+ Game Design Agent™ outline:

Course Prerequisites:

  • Basic Programming Knowledge: Familiarity with coding concepts and languages.

  • Game Design Fundamentals: Understanding of core game mechanics and structure.

  • Mathematics and Algorithms: Strong grasp of logic and problem-solving techniques.

  • Artificial Intelligence Basics: Introductory knowledge of AI principles and models.

  • Creative Thinking: Ability to envision dynamic and interactive game elements.

Modules:

Module 1: Understanding AI Agents

1.1 What are AI Agents?

1.2 Agent Architectures and Environments

1.3 Decision Making and Behavior Basics

1.4 Introduction to Multi-Agent Systems

1.5 Case Study: Pac-Man Ghost AI

1.6 Hands On: Build a Basic Reactive AI Agent Navigating a Simple Environment Using Pygame

Module 2: Introduction to AI Game Agent

2.1 What is an AI Game Agent?

2.2 Key Components of AI Game Agent

2.3 Agent Architectures

2.4 AI Game Agent Behaviors

2.5 Case Study: Racing Games (e.g., Mario Kart, Forza Horizon)

2.6 Hands-On: Creating a Simple Box Movement Game in Playcanvas

Module 3: Reinforcement Learning in Game Design

3.1 Basics of Reinforcement Learning

3.2 Key Algorithms: Q-Learning and SARSA

3.3 Applying RL to Game Agents

3.4 Challenges and Solutions in Game-based RL

3.5 Case Study: AlphaZero in Games: Mastering Chess, Shogi, and Go through Self-Play and

3.6 Hands On: Train a simple RL agent in OpenAI Gym environment

Module 4: AI for NPCs and Pathfinding

4.1 Understanding NPCs as AI Agents

4.2 Simple AI Techniques for NPCs

4.3 Pathfinding Algorithms

4.4 Obstacle Avoidance and Movement Optimization

4.5 Case Study

4.6 Hands-On

Module 5: AI for Strategic Decision-Making

5.1 Decision Trees and Minimax for Game AI

5.2 Monte Carlo Tree Search (MCTS) for AI Agent

5.3 Utility-Based Decision Making for Game AI

5.4 AI in Real-Time Strategy (RTS) Games

5.5 Case Study: StarCraft II AI by DeepMind

5.6 Hands-On: Implement a Basic MCTS Agent for Tic-Tac-Toe Using Pygame

Module 6: AI Game Agent in 3D Virtual Environments

6.1 3D Environment Representation and Challenges for AI Agents

6.2 Navigation Mesh Generation for AI Agents in 3D

6.3 Complex Agent Behaviors in 3D Worlds

6.4 Case Study: The Last of Us

6.5 Hands-On: Develop a 3D AI Agent with Navigation and Interaction in Unity Using NavMesh

Module 7: Future Trends in AI Game Design

7.1 Current and Future AI Trends

7.2 The Future of Generalist AI in Gaming

7.3 Case Study: No Man’s Sky Procedural Generation

Module 8: Capstone Project

8.1 Task Description

8.2 Practical Implementation

8.3 Testing and Debugging

8.4 Hands-On