AI of Sports Games

1. Dylan Evans Matt Kenig AI of Sports Games

2. Overview • Dead reckoning • Designing a sports game AI • In Baseball games, the main features of the AI involve: • Behaviors • The Ball Hit Event • The Ball Fielded Event

3. Dead Reckoning • Process of estimating one's current position based upon existing data • Dead reckoning algorithms help with prediction motion • Used where the human player and its AI teammates must exchange the ball or puck frequently • Also helps offset latency in online games

4. Origins of Dead Reckoning • Originally developed as a tool for navigators • A sailor used it to estimate position of ship • Given original position, intended course, speed • Did not account for outside factors • Often used to estimate enemy fleets and troops between instances of visual, radar, or spy satellite contact

5. Dead Reckoning in Sports Games • When the AI is trying to shoot the ball or puck past an active human obstacle • A soccer goalie, hockey defenseman, NFL cornerback • When the AI is trying to pass the ball or puck to the human player • In both cases, AI computes the most likely trajectory of the human player’s avatar

6. Dead Reckoning in Sports Games • In a hockey game: • AI could look at the dead reckoning parameters for both the human player and the other AIs on the ice • Determines whether the human’s current trajectory is likely to take him to an open spot shortly • If so, then AI can time a pass so that the puck will reach that spot at the same time as the player • http://www.youtube.com/watch?v=Bb4HITdpMWc&feature=related

7. Dead Reckoning in Sports Games • In a football game: • The AI calculating how to throw the ball to a human receiver will need to take the third dimension into consideration • So the ball will intercept the receiver’s trajectory at a point where it is between one meter and three meters from the ground • http://www.youtube.com/watch?v=E_s3TVzPYNU

8. Designing a Sports Game AI • Goal of the AI is to provide the user with an interactive experience that captures the abilities, personalities, and emotions of the athletes being stimulated • http://www.youtube.com/watch?v=R337lNSQizg

9. Designing a Sports Game AI • One of the first tasks is to identify the high-level decisions (called plans) that will be made • In basketball: • Pass, shoot, drive to the basket, run the play, position the defender, block a shot, etc. • We will focus on how a plan is a vital component in the whole architecture

10. AgentPlan class • Serves as a base class for all plans • Each plan has additional functions and variables unique to the particular high-level decision being managed • class AgentPlan { float EvaluateInitiation(); // how desirable it is for the plan to execute float EvaluateContinuation(); // how desirable it is for the plan to continue being used void Initiate(); // initialize decision making void Update(); // called for every iteration of the AI’s tick }

11. AgentPlan class • EvaluateInitiation() and EvaluateContinuation() return floating point values • Allows you to build a complex system where several plans can be compared against each other to determine which one should be used for the current situation • Values are usually between -1.0 and 1.0

12. AgentPlan class • i.e. Lay-up vs. jump shot • Player with basketball is a good shooter • Just stole ball, has an open breakaway down the court • We don’t want him stopping to take a jump shot, but rather want him to drive to the basket • Plan Evaluation Values: • Shot Plan -> 0.3 • Pass Plan -> -0.1 • Drive Plan -> 0.5 • http://www.youtube.com/watch?v=PCy3KYKmi0E&feature=related

13. Team Management • A way to organize the plans for the situations where they will be used • i.e. Basketball • Common states, offensive states, defensive states • Distinct responsibilities and clear transition points

14. Team Management • Offensive and defensive states: • Inbound: responsible for getting the ball in play • Transition: responsible for getting the ball into the frontcourt • Rebound: responsible for rebounding the ball after it has been shot • Etc.

15. Team Management • Common states: • Pregame: Coordinates the team and player introductions • Tip-off: coordinates the tip-off • Time-out: coordinates the time-out • Quarter break: coordinates the breaks from quarter to quarter • Etc.

16. Agent AI • Allow the actual decisions to be made • A well thought-out collection of utility functions and data used by the plans to evaluate and execute the thing they represent. • i.e. Basketball shot plan • Determine potential success chance is of the player making the shot from current location • Determine type of shot • Tell player to perform selected shot with specified success chance

17. Determining Success Chance • Need to determine the best chance of success based on the player’s skills and abilities (given by ratings values) • Determine if any penalties need to be applied (i.e. defensive pressure)

18. Choosing Shot Type • First evaluate likelihood that the player will attempt a dunk • If he cannot dunk, check for lay-up • If no lay-up, perform a jump shot

19. Command Issuing Functions • Two purposes: • Provide a place within the high-level AI to make any decisions that require more thought or logic than a simple random number • i.e. Deciding what type of dunk • Provide a wrapper to the agent mechanics

20. Agent Mechanics • Final piece of AI architecture • Manage and select the animations used • Interface between high-level and low-level AI systems • i.e. If you were giving someone who knew nothing about basketball instructions: • Walk, jog, run, pass, catch, shoot, etc.

21. Agent Cooperation in FSMs for Baseball • Sports are a classic example of object-oriented architecture • Set number of players and a ball • Players create teams • Make up a world that is governed by a set of rules • Players have predetermined behaviors • Operate within an FSM • Distinct starting and ending points • Clear transitions into other behaviors

22. Main Topics • In Baseball games, the main features of the AI involve: • Behaviors • The Ball Hit Event • The Ball Fielded Event

23. Behaviors • Enumeration of behaviors • Define what actors will be doing • Game states will be the basis for game flow

24. Behaviors • Baseball Behaviors • Divide the game into several distinct categories • Fielding • Baserunning

25. Behaviors • Baserunning Behaviors • At any given time, runners are assuming one of two behaviors • Running • Not Running • Baserunners are assigned behaviors based on events in the game such as user input or a ball being caught • Some behaviors affect the behaviors of other baserunners

26. Behaviors Go Tag Up Turn and Go Freeze Slide Turn and Look Go Back Go Halfway Possible transitions and flow for baserunning behaviors

27. Behaviors • Video example of baserunning behaviors from the game MLB 09 The Show • http://www.youtube.com/watch?v=hEJ4ie6KW5I

28. Behaviors • Fielding Behaviors • Slightly more complicated than baserunning • Two main triggers • Both lead to assignments for fielding behaviors • Ball Hit Event • Ball Fielded Event

29. Behaviors • At some point during every play, a fielder picks up the ball • Causes some behaviors to transition to others • For a non-fielder • Behavior Field Ball -> Behavior Watch • Behavior Back Up -> Behavior Watch

30. Behaviors • What to do with the ball • Every player without the ball assumes the Behavior Watch • Actor/Player with the ball becomes primary focus • Transitions to a new behavior • Throw Ball • Run With Ball • Run to Dugout

31. The Ball Hit Event • Sports are entirely event driven • In Baseball, the event that causes any action is the Ball Hit Event • All other sports have something similar • Football – Snap • Hockey – Dropping the Puck • Basketball – Jump Ball

32. The Ball Hit Event • Two main concerns when the Ball Hit Event occurs • Behavior of the fielders • Behavior of the baserunners

33. The Ball Hit Event • Basic behaviors assigned on a Ball Hit Event • Field Ball • Cover Base • Cutoff • Back Up • Assigned based specifically on where the ball is hit and the velocity at which it leaves the bat

34. The Ball Hit Event Ball Hit Event Cover Base Field Ball Back Up Cutoff Run To Dugout Run With Ball Throw Ball Watch Possible Transitions and Flow for Fielder Behaviors

35. The Ball Hit Event • An Example of Run to Dugout behavior • http://www.youtube.com/watch?v=CJ79FKUgleg(6:30)

36. The Ball Hit Event • Initial Behavior Assignments – Fielders • Ball’s initial velocity provides enough information to assign behaviors to every member on either team • Can use it to calculate the ball’s entire path • The ball’s flight is completely pre-determined from the time of impact

37. The Ball Hit Event • Each hit is categorized according to physical properties • Hit Type • Based on how the baseball was hit • Described as an application of the rule set • Hit Zone • Field is divided into 10 regions as well as two regions with negative values designated to be foul areas • Calculated using trigonometry

38. The Ball Hit Event

39. The Ball Hit Event • Once the hit type and hit zone are determined, they are used to properly determine a set of behaviors for fielders • Example • Ground ball in Zone 7 • 1st baseman and right fielder given Behavior Field Ball • 3rd baseman, shortstop, catcher, and pitcher are all given the Behavior Cover Base • 2nd baseman will receive either Behavior cutoff or Behavior Field Ball depending on the ball’s velocity • Other outfielders will be given Behavior Back Up

40. The Ball Hit Event • Behavior Assignments on Foul Balls • Hit types are more important with only two zones • Hit Type Grounder • Only have Behavior Type Watch • Hit Type Popup • Corner Infielders, Catcher -> Behavior Field Ball • Hit Type Line Drive / Hit Type Fly Ball • Corner Outfielders -> Behavior Field Ball • http://www.youtube.com/watch?v=CJ79FKUgleg (3:45)

41. The Ball Hit Event • An Example of Defense from the game MLB The Show 09: • http://www.youtube.com/watch?v=CJ79FKUgleg(1:27)

42. The Ball Hit Event • Initial Behavior Assignments – Runners • Goal of baserunners is less complicated than fielders • Advance safely around the bases and score a run • Again use Hit Type and Hit Zone to determine behavior assignment

43. The Ball Hit Event • Baserunner Cooperation • Anytime a runner enters an area approximately 20 feet in front of every base, he’ll evaluate his behavior • The runner’s process function will check: • The proximity of the closest fielder to the ball • If the ball has been fielded or thrown • Which base the ball has been thrown to • The result of this process will prompt a transition of state to either: • Turn and Go, Turn and Look, or Slide

44. The Ball Fielded Event • Throw Determination • Know where the runners were at the start of the play • Use this to determine where and how to throw the ball • Need to consider what would be realistic too • Don’t want to force a throw to 2nd base when there would be an easy out at 3rd

45. The Ball Fielded Event • Throw Determination • Fly Balls • 95% of the time the throw goes to 2nd base or Home • http://www.youtube.com/watch?v=-DH5am6-sGE • Easier to throw to the cutoff man though and then reconsider where to throw from there • Don’t have to consider the time it will take for the ball to get to the cutoff man or the base from the outfield

46. The Ball Fielded Event • Throw Determination • Rundowns • The AI always has enough information to throw out a runner with one throw in this situation • Often, the AI will allow the user to play “pickle” to make it more realistic • http://www.youtube.com/watch?v=aLXb6L6IowQ

47. The Ball Hit Event • Even though all of these events result in each agent acting separately, they all have a very common, obvious goal • Step towards intelligence

48. Questions?