What do chess, Pac-Man, and Cyberpunk 2077 have in common? These games are a good example of the evolution of AI in games. Let’s examine the development of AI games to determine our current state and future direction.
🧩 Level 1: The Scenario Era – How It All Began
Think back to the early 80s. Back then, “AI” was a fancy term for a set of “if-else” conditions. Game designers would hand-code behavior trees: “If player enters zone, then attack.”
Puzzle Piece 1:
Which classic game had ghosts with different behavior patterns that seemed intelligent but were hard-coded?
Hint: One ghost chases, another tries to ambush, one is random, and one just wanders around.
🧠 Answer: Pac-Man (1980)
Even though these planned actions were straightforward, they set the stage for the player’s interaction with the AI, establishing a sense of surprise and difficulty.
🧩 Level 2: Rise of Reactive Systems – AI Learns to Adapt
The rise of AI came in the late 90s and early 2000s. Games like Half-Life and F.E.A.R. began using finite state machines and behavior trees to simulate group tactics. Enemies would flank players, seek cover, and use grenades as their decision trees became deeper.
Meanwhile, sports games like FIFA and NBA 2K began integrating player statistics with real-time decision logic, creating more realistic opponents.
Puzzle Piece 2:
Which 2005 game had enemies dynamically adjust their behavior, creating unexpected encounters through AI scripts superimposed on the level design?
🧠 Answer: F.E.A.R.
🧩 Level 3: Modern AI – More Than Just Enemies
AI is now capable of far more than only controlling villains. Whole universes are shaped by it.
Modern uses of AI in games:
- Procedural generation: No Man’s Sky uses AI to populate planets with unique flora and fauna.
- Narrative customization: Detroit: Become Human dynamically changes its story based on your choices.
- AI directors: Left 4 Dead adjusts the intensity of the gameplay based on the player’s stress level.
Puzzle piece 3:
Which horror game uses AI to control a stalking alien that learns from your habits?
🧠 Answer: Alien: Isolation
AI controls diplomacy, economics, or a civilization’s goals in complex simulations in role-playing and strategy games.
🧩 Level 4: Mobile Intelligence – AI on iOS and Android
The mobile space is also keeping up with the times. AI in mobile games has become intelligent and effective due to advancements in chipsets and machine learning integration.
Examples:
- AI in puzzle and strategy games: mobile chess engines (e.g., Stockfish) adapt to the skill level of players in real time.
- Procedural content: With each run, endless runners alter the level’s layout using algorithms (Jetpack Joyride).
- Voice and chat AI: Some role-playing games now allow you to interact with NPCs using dialogue trees generated in natural language using AI.
Mobile AI also provides personalization: game content recommendations, analysis of player behavior, and adaptation of monetization strategies.
🧩 Final Level: Pros and Cons of AI in Games
✅ Pros:
- Replayability: Content is kept interesting by AI-generated levels and behaviors.
- Immersion: NPCs that feel “alive” increase emotional investment.
- Efficiency: AI expedites the development, testing, and debugging of resources.
- Personalization: Games adapt to individual playstyles and skill levels.
❌ Cons:
- Unpredictability: Excessive randomness in AI can disrupt game balance.
- Cost and complexity: Advanced AI requires data, training, and resources.
- Ethical risks: AI that adapts monetization too aggressively can lead to exploitative design.
🎯 Time to Play Smart: Let’s Build Your AI Game
At Melior Games, we assist customers in utilizing AI in cross-platform, PC, and mobile applications. An adaptive mobile puzzle, a self-learning enemy system in a shooter, or a procedural narrative in a role-playing game – contact us to bring your new game to life.
Want to come up with an AI game idea? Let’s figure it out together.
🧩 Discover a new level of game development with Melior Games.
📩 Contact us today to start your AI journey.
