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The Two Faces of Video Game AI Damian Isla AI Lead, Bungie Studios.

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Presentation on theme: "The Two Faces of Video Game AI Damian Isla AI Lead, Bungie Studios."— Presentation transcript:

1 The Two Faces of Video Game AI Damian Isla AI Lead, Bungie Studios

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3 Halo 3 First person shooter Epic Story Epic Combat Vehicles Physics Cooperative and Competitive Multiplayer Saved Films User-edited Levels Player-equivalent AI –in terms of abilities, not in terms of tactics!

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7 The Two Faces of AI One outwards, towards the player One inwards, toward the content creators Two interfaces with completely different, at times contradictory functions This talk General properties of these two interfaces Two examples –Behavior selection –Combat dialogue Conclusions

8 Terminology Game AI must be: Coherent Transparent –for the player –for the designer Workable

9 Player Interface

10 The Illusion of Intelligence AI seems smart, focused, lifelike –timing seems right –decisions seem reasonable –attends to the things that demand attending to –In Halo: the AI is a worthy opponent How do we sell the illusion of life and intelligence?

11 Illusion of Intelligenc e 3d ArtAnimation Game Design Scripting Decision making

12 The Fun: Transparent Decision- making Player can explain AI behavior –He dove out of the way because I threw the grenade. Player can predict AI behavior –If I throw the grenade, I bet the AI will dive out of the way. Player forms an ongoing narrative in his/her head –I threw the grenade, so he dove out of the way, and then cursed at me, and threw a grenade back, but I shot it in the air and hurt him, so he went nuts and charged me … The AI needs to facilitate / encourage that narrative

13 Designer Interface

14 Transparent Decision-making Designer can explain AI behavior –He dove out of the way because his danger_dive behavior is active. Designer can predict certain AI behavior –When I throw this grenade, theres a 75% chance hell dive out of the way Designer knows how to get different behavior –Hmm … he reacted to that grenade too quickly … I think Ill increase his projectile-acknowledgement delay from 0.5 to 0.7 seconds. Designer knows how to diagnose and fix MISbehavior –WOAH … why the hell did he do THAT?!

15 Scale The Enemy of all Transparency x 1,000 I want X to do Y when Z

16 Scale The Enemy of all Transparency The greater the variety of unique situations we need to handle well, the more complex the internal structure needed to disambiguate them, and the less expressible that internal structure is. (We might also call that competence.)

17 Transparency vs. Competence

18 Case Study 1: Behavior Selection

19 Hide? Panic? Get in that vehicle? Throw a grenade? Hold my ground?

20 Behavior A program that takes temporary control of an actor to achieve a specific goal. Fight Hide Enter vehicle Throw grenade etc. How do I decide what to do when? ~120 of these in total (i.e. ~ 7140 possible transitions)

21 Behavior FSM

22 ?? ?

23 Behavior Tree melee shoot grenad e uncove r pursue sleep fight search hide idle root cover root fight shoot

24 Behavior Tree Three Simplifications: 1.No sibling connections 2.Prioritized-list decision- scheme 3.Binary relevance functions Benefits: No more n 2 complexity Scalability

25 Behavior Tree: Designer Tools 1.Behavior Parameters 2.Masks bool hide_relevance() { if (damage > MAX_DAMAGE) { return true; } else { return false; }

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27 Players and Trees Players understands TRIGGERS, not TRANSITIONS –i.e. when the brutes armor depletes, he charges, no matter WHAT he was doing at the time Players understand priorities Players understand discrete events Players understand task-decomposition The Tree is representative of the mapping we HOPE exists in the players head

28 Lessons from Halo 2 and Halo 3 Figuring out why something happened is easy Figuring out why something DIDNT happen is still fiendishly hard

29 Case Study 2: Combat Dialogue

30 Oh no, they killed my friend! Well done, friend! Well done, Master Chief! Ha! They killed their own guy! You idiot! You killed our own guy! Oh no, I killed my own guy! Im sorry!!! Damn you, Master Chief! Aaargh!!!

31 Combat Dialogue kills Event Oh no, they killed our friend! Vocalization Match ~100 events ~320 vocalizations (and find a speaker)

32 Combat Dialogue Implementation: a rule-matching system Event: Player killed a grunt killed(a,b) prs_plr_k ill enemies(a, b), player(a) friend(a) eventvocalizati on relevance conditionsspeaker conditions 0.8

33 Combat Dialogue killed(a,b) prs_plr_k ill enemies(a, b), player(a) friend(a) 0.8 Probabilistically choose among top contenders killed(a,b) prs_ally_ kill enemies(a, b)friend(a) 0.5 killed(a,b) crs_plr_k ill enemies(a, b), player(a) enemy(a) 0.5 killed(a,b) crs_plr_b try friends(a, b), player(a)friend(a) 0.0 Implementation: a rule-matching system Event: Player killed a grunt

34 Combat Dialogue killed(a,b) prs_plr_k ill enemies(a, b), player(a) friend(a) 0.8 Probabilistically choose among top contenders killed(a,b) prs_ally_ kill enemies(a, b)friend(a) 0.5 killed(a,b) crs_plr_k ill enemies(a, b), player(a) enemy(a) 0.5 killed(a,b) crs_plr_b try friends(a, b), player(a)friend(a) 0.0 Implementation: a rule-matching system Event: Player killed a grunt

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38 Lessons from Halo 1, 2 and 3 Player is an egomaniac –Brute: Hes gone into cover! –Player: uh … no I havent. AIs need to speak consistently with each other –Marine1: I see him! –Marine 2: I dont see him! Combat dialogue serves fundamentally different functions for enemies and allies –Allies are about aural backdrop –Enemies are about information

39 Combat Dialogue Use the appropriate tools –Excel has its place Expected results were extremely soft –target was a narrative –target was negotiated between design and audio Data-mining was absolutely critical

40 But... wheres all the real AI?!

41 Real AI What about Planning Inference Genetic approaches Learning etc. … F.E.A.R (Monolith) –STRIPS Planning Black & White (Lionhead) –Decision-tree learning –Gesture recognition Euphoria (NaturalMotion) –NN + GA

42 Conclusions

43 Technique Summary Behavior Tree Rule-matching Transparency in decision-making is important Two parts to transparency: 1.Transparent algorithm 2.A tools infrastructure for editing and debugging

44 Conclusions There are two important video game AI interfaces: one out towards the player, the other in, towards the content creators. Making them agree is hard. The Holy Grail: A WYSIWIG AI Editor???

45 Thank You! Questions? Damián Isla om ?!


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