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Stavros Vassos, University of Athens, Greece   stavrosv@di.uoa.gr   May 2012




INTRODUCTION TO AI
STRIPS PLANNING
.. and Applications to Video-games!
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.
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, …)
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
Course overview
5


       Material based on the following textbooks, research
        papers, and student projects at University of Athens:
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
Artificial Intelligence and Video Games
7


       Is academic AI useful to (commercial) video games?




       Are (commercial) video games useful to academic AI?
Artificial Intelligence and Video Games
8


       Is academic AI useful to (commercial) video games?
         Academics
                  say: Yes! …
         Game developers say: No! …



       Are (commercial) video games useful to academic AI?
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
Artificial Intelligence and Video Games
10


        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)
Artificial Intelligence and Video Games
11


        Performing simple actions in the real world is difficult




     youtube link
Artificial Intelligence and Video Games
12


        Acting (and sensing) in video-game worlds is easy!
Artificial Intelligence and Video Games
13


        Acting (and sensing) in video-game worlds is easy!
        ..and AI can focus on, e.g., decision making
Artificial Intelligence and Video Games
14


        Video-game worlds feature common objects and
         realistic physics
Artificial Intelligence and Video Games
15


        Video-game worlds feature realistic navigation
         characteristics
Artificial Intelligence and Video Games
16


        Video-game worlds feature interaction with other
         characters!
Artificial Intelligence and Video Games
17


        Non Player Characters (NPCs)
Artificial Intelligence and Video Games
18


        Are video games useful to academic AI?

          AICompetitions for research problems of academic AI
           based on commercial video games
Annual Starcraft Competition at AIIDE
19


        http://webdocs.cs.ualberta.ca/~cdavid/starcraftaicomp

          Artificial
           Intelligence &
           Interactive
           Digital
           Entertainment

          Starcraft
           Real-time
           Strategy game
Annual Starcraft Competition at AIIDE
20


        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
Annual Starcraft Competition at AIIDE
21


       Krasi0   vs Skynet (2011): youtube link
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
General Game Playing Competition
23


        http://games.stanford.edu/



          You   build a program that plays chess




          So,it’s smart!
           Can it play backgammon then?
General Game Playing Competition
24


        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, …
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
Multi-agent programming contest
26


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


        http://www.multiagentcontest.org/
Artificial Intelligence and Video Games
28


        People do AI research (e.g., M.Sc., Ph.D.) based on
         techniques and results on such competitions
Artificial Intelligence and Video Games
29


        Is academic AI useful to (commercial) video games?
Artificial Intelligence and Video Games
30


        Is academic AI useful to (commercial) video games?

          Path finding
          Realistic motion

          Models of emotion

          Decision making

          Learning

          Nonlinear story telling

         …
Artificial Intelligence and Video Games
31


        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
Artificial Intelligence and Video Games
32


        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, …
Artificial Intelligence and Video Games
33


        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, …
Artificial Intelligence and Video Games
34


        Next:

          Finite   State Machines (FSMs)

          Behavior    Trees (BTs)

          Goal     Oriented Action Planning (GOAP)

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

  • 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 8  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 10  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 11  Performing simple actions in the real world is difficult youtube link
  • 12. Artificial Intelligence and Video Games 12  Acting (and sensing) in video-game worlds is easy!
  • 13. Artificial Intelligence and Video Games 13  Acting (and sensing) in video-game worlds is easy!  ..and AI can focus on, e.g., decision making
  • 14. Artificial Intelligence and Video Games 14  Video-game worlds feature common objects and realistic physics
  • 15. Artificial Intelligence and Video Games 15  Video-game worlds feature realistic navigation characteristics
  • 16. Artificial Intelligence and Video Games 16  Video-game worlds feature interaction with other characters!
  • 17. Artificial Intelligence and Video Games 17  Non Player Characters (NPCs)
  • 18. Artificial Intelligence and Video Games 18  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 19  http://webdocs.cs.ualberta.ca/~cdavid/starcraftaicomp  Artificial Intelligence & Interactive Digital Entertainment  Starcraft Real-time Strategy game
  • 20. Annual Starcraft Competition at AIIDE 20  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 23  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 24  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 26  http://www.multiagentcontest.org/
  • 27. Multi-agent programming contest 27  http://www.multiagentcontest.org/
  • 28. Artificial Intelligence and Video Games 28  People do AI research (e.g., M.Sc., Ph.D.) based on techniques and results on such competitions
  • 29. Artificial Intelligence and Video Games 29  Is academic AI useful to (commercial) video games?
  • 30. Artificial Intelligence and Video Games 30  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 31  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 32  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 33  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 34  Next:  Finite State Machines (FSMs)  Behavior Trees (BTs)  Goal Oriented Action Planning (GOAP)