129 lines
2.9 KiB
Markdown
129 lines
2.9 KiB
Markdown
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# Video Game AI
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A very coarse, practical introduction.
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## Disclaimer
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The term artificial intelligence (AI) is used to describe a hand-crafted (i.e. scripted) opponent in video games.
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In this context, the term is not related to machine learning.
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While machine learning can be leveraged to realize video game AI, we have not seen the use of such in commercial products.
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## Terminology
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- Agent: typically an AI controlled *character / actor*
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## Goal
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- Entertain the player!
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- Playing the game, adhering to the rules, using the (underlying) mechanics
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- Act natural
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## Simple AI
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> Castlevania demo
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- Can be enough for simple games
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- Often requires *design workarounds* to make challenging
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- Not very engaging
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## Big Picture
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> Glass of water
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- Emulate human thinking / behavior
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- Layers
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- Algorithms at the bottom
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- Strategy at the top
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- Usually 2 layers sufficient
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## Bottom Layer (1st)
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- Contains very basic building blocks
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- Go to position
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- Interact with object
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- …
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- Leverage algorithms
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> [Bug Algorithm](https://www.cs.cmu.edu/~motionplanning/lecture/Chap2-Bug-Alg_howie.pdf)
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> Dynamite Person Demo
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> Over Engineered Demo
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> [Overwatch Navmesh](https://youtu.be/W3aieHjyNvw?t=2946)
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> [Doom 2016 AI](https://youtu.be/3lO1q8mQrrg?t=1455)
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> Project Daredevil Demo 1
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> [Project Daredevil Demo 2](https://www.youtube.com/watch?v=pfWpMPXzBj8&list=PL7GgcoHpNOrAZ9LQBF9Rzukov59Qy7eyK&index=8)
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## Top Layer
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AI needs to:
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- be aware of game mechanics;
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- interact with game mechanics; and
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- use the *meta* of the game.
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Meta: The highest level of strategy.
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> Diabotical Demo
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- Explain general arena FPS concept
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- Non-trivial map → positioning
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- Different weapons → situational choice
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- Pickups → resources!
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- Pickups respawn → item timing
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→ more about resource management and decision making then just simply shooting each other.
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Key concept: **control**
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- In-control vs. out-of-control
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- Contested control
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## Tools
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- Bottom layer
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- Graphs
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- Control Theory
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- Top layer
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- Behavior trees
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- Decision table
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- Finite state machine
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- Async programming (co-routines)
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> https://docs.unrealengine.com/en-US/InteractiveExperiences/ArtificialIntelligence/BehaviorTrees/BehaviorTreesOverview/index.html
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## Technique
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[OODA Loop](https://en.wikipedia.org/wiki/OODA_loop):
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- Observe
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- Orient
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- Decide
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- Act
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- [In-depth explanation](https://taylorpearson.me/ooda-loop/)
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## Testing
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- Handcrafted scenarios with well defined outcome
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- AI vs. AI
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- Relate to human vs. human
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## Take Home
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**Make enemies smarter, not stronger.**
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- Good AI keeps the player entertained
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- Can be forgiving (difficulty settings)
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- Good AI plays the game similar to how a human plays the game.
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- Think in layers → concern yourself with behavior rather than algorithms
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- Leverage the OODA loop
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- [🎥 AI and Games](https://www.youtube.com/channel/UCov_51F0betb6hJ6Gumxg3Q)
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