Character AI: Sensing & Perception

Transcription

1 Lecture 22 Character AI:

2 Take Away for Today Sensing as primary bottleneck Why is sensing so problematic? What types of things can we do to improve it? Optimized sense computation Can we improve sense computation performance? Can we share sensing between NPCs? Sense event matching What are events and how are y represented? What is advantage of an event system? 2

3 Review: Sense-Think-Act Sense: Perceive world Reading game state Example: enemy near? Think: Choose an action Often merged with sense Example: fight or flee Act: Update state Simple and fast Example: reduce health? 3

4 Recall: Sensing Performance Sensing may be slow! Consider all objects Example: morale n knights, n skeletons Knights fear skeletons Proportional to # seen Count skeletons in view O(n) to count skeletons O(n 2 ) for all units Time per tick 3 units 2 units 1 unit 4

5 Recall: Sensing Performance Sensing may be slow! Consider all objects Example: morale n knights, n skeletons Knights fear skeletons Proportional to # seen Count skeletons in view O(n) to count skeletons O(n 2 ) for all units Time per tick 3 units 2 units 1 unit 5

6 Aggregation Idea taken from databases Unordered set of information Combine into single value Used in statistical analysis Examples: sum, avg, mode Decomposable Aggregates Split set up into subsets Aggregate on each subset Combine values from subsets Only for some aggregates avg = 8 (16,2) avg = 6 (12,2) avg = 8 (16,2) avg = 6 (12,2) avg = 7 (28,4) avg = 7 (28,4) avg = 7 (56,8) 6

7 Aggregation Idea taken from databases Unordered set of information Combine into single value Used in statistical analysis Examples: sum, avg, mode Decomposable Aggregates Split set up into subsets Aggregate on each subset Allows for fast parallel computation Combine values from subsets Only for some aggregates avg = 8 (16,2) avg = 6 (12,2) avg = 8 (16,2) avg = 6 (12,2) avg = 7 (28,4) avg = 7 (28,4) avg = 7 (56,8) 7

8 AI and Aggregation Trees Slide courtesy of Dave Mark Number of Allies Strength of Allies Number of Enemies Strength of Enemies Allied Strength Threat Ratio Enemy Strength Proximity to Base My Health Proximity to Leader Urgency My Morale Retreat % 8

9 AI and Aggregation Trees Slide courtesy of Dave Mark Number of Allies Strength of Allies Number of Enemies Strength of Enemies Map-Reduce Pipeline Allied Strength Do all sides at once using key-value pairs Threat Ratio Enemy Strength Urgency Proximity to Base My Health My Morale Proximity to Leader Retreat % 9

10 Influence Maps: Pathfinding and AI B A Slide courtesy of Dave Mark 10

11 Implementing Influence Maps Use pathfinding grid Track movement in square Track if friend or foe Keep count as a queue Count is sum of queue A B 1 0 Allows us to time out 1 0 Orwise, marked forever 1 Use queue as a predictor Look at rate of change Also valuable for AI Sensing is at grid, not NPC 11

12 Advantages of Influence Maps B A Influence data reflects changes Slide courtesy of Dave Mark 12

13 Advantages of Influence Maps B Add a priori assumptions A Slide courtesy of Dave Mark 13

14 Sensing: Perception Groups Vision: limited field of view Gives exact object location, information Limited by obstacles and range Little information (motion) at periphery Sound: omni-directional Gives direction & distances Requires you track sounds actions make Smell: omni-directional No direction or distance; proximity only Requires you track smells actions make 14

15 Sensing: Line-of-Sight 15

16 Sensing: Line-of-Sight 16

17 3D Line-of-Sight: Ray Casting 17

18 3D Line-of-Sight: Ray Casting 18

19 3D Line-of-Sight: Ray Casting 19

20 Sense Events Event: encoded sense data Tagged with sense type Pre-aggregated information Information self-contained Object with methods Class is sense type Sensing is event matching Each event has a type NPCs register for a type Send NPC registered events Check if event is relevant! Event: CharacterExposed! boolean isseen(npc guard); float distanceto(npc guard); Vector movedirection(); 20

21 Sense Event Matching sound sight sound Register events of interest Event Handler Game Loop sound smell 21

22 Sense Event Matching Notify of any matching events Event Handler Game Loop Check for any matching events 22

23 Sense Event Matching Notify of any matching events Event Handler Advantage: Sensing is Global, Not Local Game Loop Check for any matching events 23

24 Representing Events Lightweight Heavyweight Memory Player Memory Player CharacterExposed Reference to player CharacterExposed Copy of player 24

25 Representing Events Lightweight Heavyweight class Event {" Player ref;" Event(Player p) {" ref = p;" }" } Advantages Fast to create event No additional memory class Event {" Player ref;" Event(Player p) {" ref = p.copy();" }" } Advantages Stores past events Can be communicated 25

26 Simple Pub/Sub Architecture NPC Hashtable Event types are keys Values are lists of NPCs! tag1 Say NPC subscribes to e Each update cycle Generate all of events tag2 Complex Pub/Sub Query System System Game Loop Get NPCs for each event tag1, tag3 Send those events to NPC Process NPCs normally tag4 26

27 Simple Pub/Sub Architecture tag1 NPC Behavior tag2 Complex Pub/Sub Query System System Game Loop tag1, tag3 tag4 27

28 Restrict to nearby NPCs Have detection range Limits events sensed Spatial Optimizations Easy to combine with event matching system Works in both directions Nimbus: can see radius Aura: can be seen radius Area of interest management 28

29 Case Study: Thief Series 29

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31 Line-of-Sight in Thief Long Distance Focused View Motion Detection Peripheral Vision Short Distance 31

32 Sounds in Thief Easier than vision Primarily distance-based Decays probabilistically Tag with level of interest Sounds can be blocked Not same as line-of-sight Use alternate level map Or tag your visible map Not physically realistic Echoes? Reflections 32

33 Sounds in Thief Sounds are general purpose Resuable framework Code is lightweight Encodes or senses Example: Smell Treated as pseudo-sound Generate like any sound * sniff * Again, ignores or factors * sniff * Wind direction Masking smells 33

34 Representing Events Lightweight Heavyweight class Event {" Player ref;" Event(Player p) {" ref = p;" }" } Advantages Fast to create event No additional memory class Event {" Player ref;" Event(Player p) {" ref = p.copy();" }" } Advantages Stores past events Can be communicated 34

35 Communicating Senses First Hand LOS Sight & Sound First Hand LOS Sight & Sound Second Hand Sight & Sound? 35

36 Alertness: Active Senses High Alert First Hand LOS Sight & Sound Medium Alert First Hand LOS Sight & Sound Second Hand Sight & Sound High Alert First Hand Sound 36

37 Thief: Sense Events and Aggregation Position Lighting Movement Exposure Sound System Visibility Sound Queue Viewcone Selector Viewcone Non-specific Spatial Events Look Listen Sense Pulse Receiver Game Mechanics and Configuration Inter-Agent Communication Ramp Up Delay Cool-down Capacitor Inter-Agent Observation 37 Sense Links

38 Summary Sensing is most expensive part of AI Each character looks at every object in game Often leads to O(n 2 ) behavior (bad!) Can optimize sense garing Aggregation is amenable to parallelization Can piggyback some data onto pathfinding Event matching inverts sensing problem Creation of sense makes a data event Forward event to relevant NPCs 38