2. RECAP CSE 348 AI Game Programming Héctor Muñoz-Avila

3. Course Goal Our goal was to understand the connections and the misconceptions from both sides AI research A C B ABC AC B C B A B A C B A C BC A C A B A C B B C A AB C A B C A B C “AI” as game practitioners implemented it projects (me) (you)

4. Controlling the AI Opponent: FSMs FSM: States, Events and Actions Stack Based FSM’s Polymorphic FSM Multi-tier FSM Spawn D Wander ~E,~S,~D ~E D Attack E,~D ~E E E D ~S Chase S,~E,~D E S S D Soldier RiflemanOfficer BritishSoviet AmericanGerman Machine Gunner BritishSoviet AmericanGerman BritishSoviet AmericanGerman Robocode Planning Operators Patrol  Preconditions: No Monster  Effects: patrolled Fight  Preconditions: Monster in sight  Effects: No Monster PatrolFight Monster In Sight No Monster FSM: A resulting plan: Patrol patrolled Fight No Monster Monster in sight (Finite State Machines in Games (Stanislav Tsanev)

5. Controlling the AI Opponent: HFSMs UT task: Domination Strategy: secure most locations UT action: move Bot1 to location B Strategic Intelligence Level 1 Operational Intelligence Level 2 Tactical Intelligence Level 3 Individual Unit Level 4 Achieving gaming goals (Kellen J. Gillespie)

6. Controlling AI Opponent: Scripting Scripting Languages (Justin Scripting Languages (Justin Karneeb) Wargus  Learning (Matt Dilts) 5 Training script 1 Training script 2 …. Training script n Counter Strategy 1 Counter Strategy 2 …. Counter Strategy n Evolutionary Algorithm Evolve Domain Knowledge Knowledge Base Revision Manually Extract Tactics from Evolved Counter Strategies Combat team controlled by human player team controlled by computer A B 1.What is a scripting Language? extends the use of another language or piece of software. 2. Parallel development 3.Pros Modding Easy to understand 4.Cons Less functionality

7. Controlling AI Opponent: Team Squad Tactics (Bryan Auslander) Dead Reckoning Predicting future state For games: Newton physics Estimate future trajectory: Kinematics Sports Games (Chris Wojciechowski) Identify high-level decisions decentralized centralized

8. Path-Finding Navigation () Navigation (Jeremy David Christman) Navigation set hierarchy Interface tables Reduction memory Increase performance A* (Joseph Siefers)

9. Game Genres First-Person Shooters Animation makes sure that animation fits situation Combat Possibly most important subsystem Behavior Highest level, has precedence over other systems Movement Determine how to move (path finding) (Xavier Otero Keil) Unreal Tournament Racing games (Emily Cohen) Racing vehicle control Multi-layer system Each layer defines behavior Optimal racing line Use of Newton physics

10. Game Genres RTS: reel tyme strattagees So, what is it? Formations Rally/Waypoints Multi-Tiered AI Layers Terrain analysis using hierarchy Architecting an RTS AI Economies Goal cost vs task cost Bonus feature on spell casting (Dave Heefner) Wargus Role Playing Games Combat systems Turn-based Real time Expansive worlds Common elements Technical aspects (Nick Moukhine)

11. Other Crucial Topics Player Modeling Manually Adaptive AI  Most commonly used What is player modeling?  Keeps track of user’s actions  Initializing the model  Updating the model traitValue= α*observedValue + (1- α)*traitValue (James Morrison) Camera Control Raycast collisions  Cast out one ray from the character to the camera  This causes sudden camera movements Multi-raycast  Send out four rays from the character around where the camera should go (Christopher M. Hinkey)

12. Other Crucial Topics NPC Behavior D&D origins General NPC goals (“fun”) Hard-scripted versus autonomous behaviour (Jonathan Michael Ziegler ) Map, World, Wall generation Generating maps  What do we want in a map? Warcraft 3 map editor  RTS maps for Empire Earth Wall Building  Generating intelligent barriers Populating large worlds using limited resources  The Waterfall Algorithm (Mercer, Jonathan C.)

13. Other Crucial Topics Story line, drama Problems in video game drama HTN Planning for game story lines Five Factor Model (FFM) Openness to experience, Conscientiousness, Extraversion, Agreeableness, Neuroticism (Brander, Gregory M) Crowd/swarm simulations Swarm Intelligence  Flocking  Basic  Steering  Swarms Applications  Animals  Vehicles  People (Kristen Gardner)

14. 2008 Hall of Fame Project # 1. Robocode. Tournament winner: Aperture Science (Hinkey, Christopher M.; Karneeb, Justin T.; Gillespie, Kellen J). Project # 2. Unreal Tournament. Tournament winner: Aperture Science (Hinkey, Christopher M.; Karneeb, Justin T.; Gillespie, Kellen J). Innovation winner: Reretaliate (Brander, Greg; Moukhine, Nick; Wojciechowski, Chris). Project # 3. Call To Power 2. Tournament winner: Act-Fail (Morrison, J., Ziegler, J., Auslander, B.). Innovation winner: Aperture Science (Hinkey, Christopher M.; Karneeb, Justin T.; Gillespie, Kellen J). Project # 4: Wargus Tournament winner: We will learn soon!

15. Acknowledgements All of you: –Presentations were very good –Projects were worked well (despite difficulties) –All master groups made their projects work –Changes for future iterations of this course: Work on complete Java model for CTP2

16. Final Summary AI research A C B ABC AC B C B A B A C B A C BC A C A B A C B B C A AB C A B C A B C “AI” as game practitioners implemented it A* AI Planning  HTN Planning Machine learning  Reinforcement learning  Dynamic scripting Fuzzy logic Knowledge representation  Rule-based systems Programming Finite State Machines Scripting languages Genres First-person shooter  Squad tactics Real-time strategy Racing games Team sports Role-playing games  NPC behavior Path finding Look-up tables Waypoints Other crucial topics Camera control Player modeling Story line, drama Swarm simulations Map generation