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Intro to AI STRIPS Planning & Applications in Video-games Lecture1-Part1
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Intro to AI STRIPS Planning & Applications in Video-games Lecture1-Part1

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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 …

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

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  • 1. Stavros Vassos, University of Athens, Greece stavrosv@di.uoa.gr May 2012INTRODUCTION TO AISTRIPS PLANNING.. and Applications to Video-games!
  • 2. Course overview2  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 overview3  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 overview4  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 overview5  Material based on the following textbooks, research papers, and student projects at University of Athens:
  • 6. Course overview6  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 Games7  Is academic AI useful to (commercial) video games?  Are (commercial) video games useful to academic AI?
  • 8. Artificial Intelligence and Video Games8  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 Games9  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 Games10  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 Games11  Performing simple actions in the real world is difficult youtube link
  • 12. Artificial Intelligence and Video Games12  Acting (and sensing) in video-game worlds is easy!
  • 13. Artificial Intelligence and Video Games13  Acting (and sensing) in video-game worlds is easy!  ..and AI can focus on, e.g., decision making
  • 14. Artificial Intelligence and Video Games14  Video-game worlds feature common objects and realistic physics
  • 15. Artificial Intelligence and Video Games15  Video-game worlds feature realistic navigation characteristics
  • 16. Artificial Intelligence and Video Games16  Video-game worlds feature interaction with other characters!
  • 17. Artificial Intelligence and Video Games17  Non Player Characters (NPCs)
  • 18. Artificial Intelligence and Video Games18  Are video games useful to academic AI?  AICompetitions for research problems of academic AI based on commercial video games
  • 19. Annual Starcraft Competition at AIIDE19  http://webdocs.cs.ualberta.ca/~cdavid/starcraftaicomp  Artificial Intelligence & Interactive Digital Entertainment  Starcraft Real-time Strategy game
  • 20. Annual Starcraft Competition at AIIDE20  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 AIIDE21  Krasi0 vs Skynet (2011): youtube link
  • 22. Ms Pac-Man vs Ghost Team Competition22  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 Competition23  http://games.stanford.edu/  You build a program that plays chess  So,it’s smart! Can it play backgammon then?
  • 24. General Game Playing Competition24  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 contest25  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 contest26  http://www.multiagentcontest.org/
  • 27. Multi-agent programming contest27  http://www.multiagentcontest.org/
  • 28. Artificial Intelligence and Video Games28  People do AI research (e.g., M.Sc., Ph.D.) based on techniques and results on such competitions
  • 29. Artificial Intelligence and Video Games29  Is academic AI useful to (commercial) video games?
  • 30. Artificial Intelligence and Video Games30  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 Games31  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 Games32  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 Games33  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 Games34  Next:  Finite State Machines (FSMs)  Behavior Trees (BTs)  Goal Oriented Action Planning (GOAP)