Add game AI notes

topic/game_ai/notes.md

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