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AI+ Game Design Agent Specialty (AP-6012)

Modern games rely on AI to create smarter characters, adaptive environments, and more responsive player experiences.

AI+ Game Design Agent Specialty explores how intelligent agents can support NPC behaviour, pathfinding, reinforcement learning, and strategic decision-making. You’ll also build AI-driven game agents across 2D and 3D environments and apply these skills in a practical capstone project.

Overview

Overview

AI agents can make game worlds feel more dynamic by allowing characters and systems to respond intelligently to players. This course introduces the foundations of AI agents and shows how they are applied in modern game development.

You’ll explore agent architectures, reinforcement learning, NPC behaviour, pathfinding, strategic decision-making, and AI in 3D environments.

The course also covers emerging approaches such as procedural content generation, adaptive gameplay, and generalist AI models. Hands-on activities use game development frameworks to help you build, test, and improve working AI agents.

Prerequisites
  • Basic programming knowledge and familiarity with coding concepts

  • Understanding of core game mechanics and game structure

  • Basic knowledge of mathematics, algorithms, and logical problem-solving

  • Introductory understanding of artificial intelligence

  • Creative thinking for designing interactive and adaptive game experiences

Target Audience
  • Game designers looking to integrate AI into game mechanics and player experiences

  • Game developers interested in intelligent characters and procedural content generation

  • AI enthusiasts exploring applications of AI in gaming

  • Aspiring game creators building foundational AI game design skills

  • Technology innovators interested in adaptive and intelligent gameplay systems

Exam Blueprint
  • Understanding AI Agents – 7%
  • Introduction to AI Game Agent – 15%
  • Reinforcement Learning in Game Design – 15%
  • AI for NPCs and Path Finding – 15%
  • AI for Strategic Decision-Making – 12%
  • AI Game Agent in 3D Virtual Environments – 12%
  • Future Trends in AI Game Design – 12%
  • Capstone Project – 12%
FAQs

1. Will I build AI agents for games during the course?
Yes, the course includes practical activities for creating agents, implementing behaviours, training reinforcement learning models, and working in game environments.

2. Can the course be taken online?
Yes, the course is available through live virtual instructor-led training or a self-paced online option.

3. Is in-person training available?
Yes, classroom sessions are available through AI CERTs Authorized Training Partners.

Course Outline

Module 1: Understanding AI Agents
  1. AI Agent Fundamentals
  2. AI Agent Definitions
  3. Agent Architectures
  4. Reactive Agents
  5. Hybrid Agents
  6. Agent Environments
  7. Perception and Interaction
  8. AI Decision-Making
  9. Agent Goals and Actions
  10. Multi-Agent Systems
  11. Agent Collaboration and Competition
  12. Case Study: Pac-Man Ghost AI

 

Module 2: Introduction to AI Game Agent
  1. Introduction to AI Game Agents
  2. AI Agents for NPC Behaviour
  3. Perception in Game Agents
  4. Decision-Making
  5. Agent Actions
  6. Reactive Architectures
  7. Deliberative Architectures
  8. Hybrid Architectures
  9. Patrolling Behaviour
  10. Chasing Behaviour
  11. Attacking Behaviour
  12. Behaviour Modelling Across Game Genres

 

Module 3: Reinforcement Learning in Game Design
  1. Reinforcement Learning Fundamentals
  2. Rewards and Penalties
  3. Adaptive Game Agents
  4. Q-Learning
  5. SARSA
  6. Reinforcement Learning for Game Decisions
  7. Exploration vs. Exploitation
  8. Challenges in Game-Based Reinforcement Learning
  9. AlphaZero Case Study
  10. Strategic Game Applications
  11. Hands-On: Train a Reinforcement Learning Agent in OpenAI Gym

 

Module 4: AI for NPCs and Path Finding
  1. NPCs as AI Agents
  2. NPC Decision-Making
  3. Finite State Machines
  4. Behaviour Trees
  5. Pathfinding Algorithms
  6. A* Pathfinding
  7. Obstacle Avoidance
  8. Movement Optimization
  9. NPC Patrol Behaviour
  10. NPC Chase Behaviour
  11. Case Study
  12. Hands-On NPC Development

 

Module 5: AI for Strategic Decision-Making
  1. Strategic Decision-Making in Games
  2. Decision Trees
  3. Minimax Algorithm
  4. Monte Carlo Tree Search
  5. Utility-Based Decision-Making
  6. Real-Time Strategy Game AI
  7. Dynamic AI Strategies
  8. Predicting Game Outcomes
  9. Adaptive Opponent Behaviour
  10. Hands-On: Build an MCTS Agent for Tic-Tac-Toe

 

Module 6: AI Game Agent in 3D Virtual Environments
  1. AI Agents in 3D Game Worlds
  2. 3D Environment Representation
  3. Navigation in 3D Environments
  4. Navigation Mesh Generation
  5. 3D Pathfinding
  6. Complex Agent Behaviours
  7. Tactical Decision-Making
  8. Environmental Interaction
  9. Unity
  10. C#
  11. AI Game Maker
  12. Hands-On: Build a 3D AI Agent with Navigation and Interaction

 

Module 7: Future Trends in AI Game Design
  1. Machine Learning-Driven NPCs
  2. Procedural Content Generation
  3. Generalist AI Models
  4. Dynamic Game Worlds
  5. Adaptive Difficulty
  6. Personalized Player Experiences
  7. Adaptive Storytelling
  8. AI as a Creative Partner
  9. No Man’s Sky Example
  10. Resident Evil 4 Example
  11. Future AI-Driven Gaming Experiences

 

Module 8: Capstone Project
  1. Design an AI Game Agent
  2. Build the Agent Using Unity3D, Playcanvas, or Pygame
  3. Implement Navigation
  4. Implement Obstacle Avoidance
  5. Apply Reinforcement Learning
  6. Develop Agent Behaviours
  7. Integrate the Agent into a Game Environment
  8. Test Agent Performance
  9. Debug Agent Behaviour
  10. Optimize the AI Agent
  11. Complete the End-to-End Game Agent Development Cycle
Note : A representative from Datacipher will contact you with further details
Payment Methods

At DataCipher, we offer a variety of payment options for our Fortinet courses. Here are the methods available:

Purchase Order (PO) – If your organization prefers using a purchase order, begin the registration process by clicking the Register button. At the conclusion of the registration form, choose the option “My company will pay for it, please send an invoice with the payment details.” Our training team will then provide an official quote and any necessary additional information that your accounts department might need to issue the PO.

Bank Transfer – DataCipher maintains bank accounts in both the US and Europe, accommodating all standard bank transfer methods such as IBAN/BIC, Swift, ACH, or wire transfer. To make a payment via bank transfer, simply use the Register button to sign up for your selected course.

Credit Card Payments – We accept payments from all major credit cards, including Mastercard, VISA, American Express, Discover & Diners, and Cartes Bancaires. Payments can be made directly through the registration link or by requesting an invoice that includes a web link for online payment. All transactions are secure, and DataCipher does not store any credit card information.

These options are designed to make the registration process as smooth and flexible as possible for all participants.

Status

Guaranteed to Run – DataCipher is committed to running this class unless unforeseen events such as an instructor’s accident or illness occur.

Guaranteed on Next Booking – The course will proceed once an additional student registers.

Scheduled Class – We have scheduled this course and rarely cancel due to low enrollment. We offer a “Cancel No More Than Once” guarantee, ensuring that if a class is canceled due to insufficient enrollment, the next session will run regardless of the number of attendees.

Sold Out – If the class is fully booked, please use our contact form to join the waiting list or to inquire about additional sessions. We’re here to accommodate your training needs and keep you informed of new opportunities.

Half and Full-Day Training

At DataCipher, we offer our training courses in both traditional full-day and convenient half-day formats. Our half-day classes are specifically designed for IT professionals who cannot be away from their workplaces for consecutive full days. This flexible schedule allows participants to dedicate a few hours to learning and then return to their regular work responsibilities.

The curriculum for both the full-day and half-day formats is identical. The primary difference is that the half-day classes spread the coursework over a more extended period, providing a balanced approach to professional education. DataCipher has been successfully running these half-day training sessions for several years, receiving consistently positive feedback from our customers. They appreciate the flexibility and report that the extended timeframe facilitates a deeper understanding of the material, as it gives them more time to absorb and reflect on the information learned.

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