Use cases in games

Reinforcement learning can be used to enhance a video game in many ways. Below are some examples of how you can use RL in a game.

1. Create more engaging games

RL can create more human-like behaviors and emotions to make your game feel more alive. You can also use RL to change your game mechanics in real-time and build different ways for your players to interact with your game.

2. Bot development

Use RL to create clever NPCs and enemies to make your game feel more realistic. You can create bots to master game strategies and defeat professional video game players. Bots can also be used to help with things like level difficulty analysis and QA, as mentioned below.

3. Level difficulty analysis

Create bots that play through a game to make sure that the difficulty of a level is optimized. If your level is too hard, players will get frustrated and stop playing. If your level is too easy, players will not be engaged. Use RL to optimize your game level difficulty in an automated fashion instead of doing it manually.

4. Better QA

Create bots that help identify defects and difficulties in game level design. Use RL to do heuristic QA by testing algorithms and probabilities in your game.