This is a short course that aims to provide an introduction to the techniques currently used for the decision making of non-player characters (NPCs) in commercial video games, and show how a simple deliberation technique from academic artificial intelligence research can be employed to advance the state-of-the art. For more information and downloading the supplementary material please use the following links: http://stavros.lostre.org/2012/05/19/video-games-sapienza-roma-2012/ http://tinyurl.com/AI-NPC-LaSapienza

1. Stavros Vassos, University of Athens, Greece stavrosv@di.uoa.gr May 2012
INTRODUCTION TO AI
STRIPS PLANNING
.. and Applications to Video-games!

2. Course overview
2
 This course aims to
 Provide an introduction to the AI techniques currently
used for the decision making of non-player characters
(NPCs) in commercial video games
 Show how a simple AI technique from academic
research (STRIPS planning) can be employed to
advance the state-of-the art.

3. Course overview
3
 This course aims to
 Get you started with doing a research/programming
project related to AI and video games!
 Using AI tools for STRIPS planning
 Using state-of-the-art game engines such as Unity3D and
Source Engine (Half-life, Counter Strike, …)

4. Course overview
4
 Lecture 1: Game-inspired competitions for AI research,
AI decision making for non-player characters in games
 Lecture 2: STRIPS planning, state-space search
 Lecture 3: Planning Domain Definition Language (PDDL),
using an award winning planner to solve Sokoban
 Lecture 4: Planning graphs, domain independent
heuristics for STRIPS planning
 Lecture 5: Employing STRIPS planning in games:
SimpleFPS, iThinkUnity3D, SmartWorkersRTS
 Lecture 6: Planning beyond STRIPS

5. Course overview
5
 Material based on the following textbooks, research
papers, and student projects at University of Athens:

6. Course overview
6
 Lecture 1: Game-inspired competitions for AI research,
AI decision making for non-player characters in games
 Lecture 2: STRIPS planning, state-space search
 Lecture 3: Planning Domain Definition Language (PDDL),
using an award winning planner to solve Sokoban
 Lecture 4: Planning graphs, domain independent
heuristics for STRIPS planning
 Lecture 5: Employing STRIPS planning in games:
SimpleFPS, iThinkUnity3D, SmartWorkersRTS
 Lecture 6: Planning beyond STRIPS

7. Artificial Intelligence and Video Games
7
 Is academic AI useful to (commercial) video games?
 Are (commercial) video games useful to academic AI?

8. Artificial Intelligence and Video Games
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 Is academic AI useful to (commercial) video games?
 Academics
say: Yes! …
 Game developers say: No! …
 Are (commercial) video games useful to academic AI?

9. Artificial Intelligence and Video Games
9
 Is academic AI useful to (commercial) video games?
 Academics
say: Yes! …
 Game developers say: No! …
 Are (commercial) video games useful to academic AI?
 Puzzle games: complex logical problems
 Strategy games: complex resource management and
decision making problems
 First-person games: non-player characters as autonomous
agents

10. Artificial Intelligence and Video Games
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 Are (commercial) video games useful to academic AI?
 Often, the real-world problems are too difficult/complex
to handle
 Video games offer a level of abstraction that allows the
AI academic community to experiment focusing on one
aspect of the problem each time
 E.g., think of an autonomous robotic bartender
 In a bar in Rome
 In a controlled environment specifically for this purpose
 In a MMORPG (massively multiplayer online RPG)

11. Artificial Intelligence and Video Games
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 Performing simple actions in the real world is difficult
youtube link

12. Artificial Intelligence and Video Games
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 Acting (and sensing) in video-game worlds is easy!

13. Artificial Intelligence and Video Games
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 Acting (and sensing) in video-game worlds is easy!
 ..and AI can focus on, e.g., decision making

14. Artificial Intelligence and Video Games
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 Video-game worlds feature common objects and
realistic physics

15. Artificial Intelligence and Video Games
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 Video-game worlds feature realistic navigation
characteristics

16. Artificial Intelligence and Video Games
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 Video-game worlds feature interaction with other
characters!

17. Artificial Intelligence and Video Games
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 Non Player Characters (NPCs)

18. Artificial Intelligence and Video Games
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 Are video games useful to academic AI?
 AICompetitions for research problems of academic AI
based on commercial video games

19. Annual Starcraft Competition at AIIDE
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 http://webdocs.cs.ualberta.ca/~cdavid/starcraftaicomp
 Artificial
Intelligence &
Interactive
Digital
Entertainment
 Starcraft
Real-time
Strategy game

20. Annual Starcraft Competition at AIIDE
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 http://webdocs.cs.ualberta.ca/~cdavid/starcraftaicomp
 Brood War Application Programming Interface
 C++ API
 Retrieve information about the state of the game
 Control units and buildings
 http://code.google.com/p/bwapi/
 Registration deadline: 1 July

21. Annual Starcraft Competition at AIIDE
21
 Krasi0 vs Skynet (2011): youtube link

22. Ms Pac-Man vs Ghost Team Competition
22
 http://www.pacman-vs-ghosts.net
 Builda program that controls
Ms Pac-Man or one of the ghosts
 The game server transmits the state
of the game as an image, 15 times
per second
 Java API
 Registration deadline: 27 May

23. General Game Playing Competition
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 http://games.stanford.edu/
 You build a program that plays chess
 So,it’s smart!
Can it play backgammon then?

24. General Game Playing Competition
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 http://games.stanford.edu/
 Build a program that plays board games.. all of them!
 Inthe beginning of each match the program receives a
description of the game to play in a language that
resembles PDDL
 C++, Java, Prolog API, …

25. Multi-agent programming contest
25
 http://www.multiagentcontest.org/
 Emphasis on multi-agent systems
 Since 2005 with different scenarios every year that
force agents to work as a team

26. Multi-agent programming contest
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 http://www.multiagentcontest.org/

27. Multi-agent programming contest
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 http://www.multiagentcontest.org/

28. Artificial Intelligence and Video Games
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 People do AI research (e.g., M.Sc., Ph.D.) based on
techniques and results on such competitions

29. Artificial Intelligence and Video Games
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 Is academic AI useful to (commercial) video games?

30. Artificial Intelligence and Video Games
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 Is academic AI useful to (commercial) video games?
 Path finding
 Realistic motion
 Models of emotion
 Decision making
 Learning
 Nonlinear story telling
…

31. Artificial Intelligence and Video Games
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 Is academic AI useful to (commercial) video games?
 Let’s focus on
 Games with non-player characters (NPCs)
 E.g., First-Person Shooter (FPS) games
 The decision making process of an NPC

32. Artificial Intelligence and Video Games
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 Video Games:
 Finite State Machines
 Decision Diagrams
 Behavior Trees
 Goal Oriented Action Planning
 Academic AI on agents:
 Knowledge representation, First-order logic,
Classical planning, Planning with preferences, …
 Belief-Desire-Intention architecture, Agent-based
programming, …
 Probabilistic reasoning, Bayesian networks,
Utility theory, Markov Decision Processes, …

33. Artificial Intelligence and Video Games
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 Video Games:
 Finite State Machines
 Decision Diagrams
 Behavior Trees
 Goal Oriented Action Planning
 Academic AI on agents:
 Knowledge representation, First-order logic,
Classical planning, Planning with preferences, …
 Belief-Desire-Intention architecture, Agent-based
programming, …
 Probabilistic reasoning, Bayesian networks,
Utility theory, Markov Decision Processes, …

34. Artificial Intelligence and Video Games
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 Next:
 Finite State Machines (FSMs)
 Behavior Trees (BTs)
 Goal Oriented Action Planning (GOAP)