1. Artificial Intelligence in Games Week 7
Steve Rabin

2. Pathfinding Integration Project
How did it go?
Any problems?
How much time did it take?

3. Euphoria Demo

4. Tactics and Terrain Analysis

5. Terrain Analysis Algorithmic analysis of terrain In general:
Automated with no human intervention
Alternative to hard-coding regions of interest
In general:
Are there spots on the terrain that are advantageous to me?
How can these be determined algorithmically?
Given the current terrain, how can I tease out this info?

6. Terrain Analysis: Real-Time Strategy Games
What are static points of interest on an RTS map?
What are dynamic points of interest during an RTS battle?

7. Terrain Analysis: Real-Time Strategy Games
Chokepoints
Barriers force units through narrow path
Barriers can be cliffs, walls, water, etc.
Ambush sites
High terrain overlooking low terrain chokepoint
Wall building sites
Low cost for building walls
Natural barriers so not much wall required
Cliffs
Water
Edge of map
Identify front of the battle
Identify flanking routes
Identify inferior forces

8. Terrain Analysis: First-Person Shooter Games
What are static points of interest in an FPS map?
What are dynamic points of interest during an FPS fight?

9. Terrain Analysis: First-Person Shooter Games
Cover points
Shielding
Darkness
Sniper points
Good cover point (shielding, darkness)
Potential high visibility to a large area
Rear coverage
Height advantage
Escape route
Safe paths to move from area to area
Low casualties in path
Low visibility to other areas
Good cover along path
Line-of-sight vulnerability
Stay out of other's line-of-sight

10. Tactical Reasoning in a First-Person Shooter
Visibility is a good tactical indicator
Does spot provide cover?
Front cover and rear cover?
How safe is it?
Does spot provide accessibility?
Is a given spot good to shoot from?
Can we escape easily?
How dangerous is it?

11. Tactical Reasoning with Waypoints: Half-Life 2 (first-person shooter)
Implementation strategy:
Preprocess terrain, storing visibility info
Can area A see area B?
Store visibility info in waypoint nodes
Node A’s ability to see every other node
How would you store it?

12. Tactical Reasoning with Waypoints: Storing Visibility Information
Store visibility info with bit strings
Can perform operations on groups
and or
not

13. Tactical Reasoning with Waypoints: Safe and Dangerous Nodes
Which locations are
Potentially safe?
Potentially dangerous?
Safe pathfinding
Penalize dangerous nodes
These are node visibilities
What about the actual enemies?

14. Tactical Reasoning with Waypoints: Attack Positioning
Visible nodes
Show where you could attack from
But no cover
Better strategy
Find a node to attack enemy X from
Which is also shielded from other enemies

15. Tactical Reasoning with Waypoints: Attack Positioning
1. Get nodes visible to selected enemy
2. Get nodes visible to other enemies
3. Get safe nodes to attack from: 3 = 1 & !2

16. Tactical Reasoning with Waypoints: Attack Positioning
Other strategies
Take cover from everyone
Find a safe node that is close to a completely safe node (in case NPC needs to reload)
Flanking
Eliminate attack points that the enemy is facing
For sneaking up on enemies

17. Tactical Reasoning with Waypoints: Static Waypoint Analysis
Determine danger of each node in a static environment
Weight each node based on number of nodes that can see it
If pathfinding takes into consideration
Paths are less likely to be visible to enemies

18. Tactical Reasoning with Waypoints: Static Waypoint Analysis
Nodes marked for visibility count
Sniper nodes have high exposure next to nodes with low exposure

19. Tactical Reasoning with Waypoints: Pinch Points and Squad Tactics
Identify pinch points as ambush spots
1. Find node (N) with only two neighbors
2. One neighbor node must be in confined area
3. Nodes connected to other neighbor nodes are ambush spots

20. Tactical Reasoning with Waypoints: Limitations
Must use hierarchy of networks to reduce size of bit strings
Ducking action can make some nodes both good cover and good attack locations
Annotate these nodes
Unidirectional connections makes it a little more complicated
Density of waypoints impacts quality of reasoning

21. Influence Mapping

22. Influence Mapping Abstracts distribution of power
2D grid superimposed on terrain
Unit strength is summed into grid cells
Influence declines exponentially with distance
Helps determine
Weaknesses
Neutral routes to flank enemy
The “front” of the battle

23. Influence Mapping: Basic Influence Map

24. Influence Mapping: Engagement

25. Influence Mapping: Analysis of Options

26. Influence Maps: Other Uses
SimCity
Non-violent use
Influence of crime, pollution, police, fire stations, etc

27. Spatial Database for Spatial Analysis

28. Spatial Database for Spatial Analysis
Generalize “terrain reasoning with waypoints”
Use a grid instead
Expand to capture dynamic features
Capture other interesting aspects

29. Spatial Database for Spatial Analysis: Many Layers of Grids
Visibility
How many squares are visible
Openness layer
Proximity to static obstacles
Cover layer
Locations where AI can take cover from gunfire
Area occupancy layer
Number of units in an area
Line-of-fire layer
Direction that weapons are being aimed
Light level layer
Brightness or darkness of any spot
Area search layer
Spots that have been searched

30. Spatial Database for Spatial Analysis: Openness Layer

31. Spatial Database for Spatial Analysis: Area Occupancy Layer

32. Spatial Database for Spatial Analysis: Line-of-Fire Layer

33. Spatial Database for Spatial Analysis: Combine Layers
Combat desirability layer
Represents desirability of moving into any given area in combat
Combines openness, static cover, area occupancy layers

34. Project 3: Implement Terrain Analysis
Due next week (May 19th)
(100%) Create at least 3 simple layers of grids and 1 combined layer that can be toggled through (with the "L" key)
Possible layers: Openness Layer, Occupancy Layer, Line-of-Fire Layer, Cover Area Layer, Area Search Layer, and Combat Desirability Layer
Extra Credit: (10%) Have the agents use the information to do something intelligent

35. Squad Tactics

36. Squad Tactics: Decentralized vs Centralized

37. Squad Tactics: Decentralized Squad

38. Squad Tactics: Decentralized Squad
Key points:
Extension of individual AI
Easy to add to existing AI
Robustly handles many situations
Deals well with a variety of capabilities within the team
Can be easily combined with scripted squad member actions
Cooperation and group behavior emerges from individual behaviors
Technique used in original Half-Life

39. Squad Tactics: Decentralized Squad
void SoloAI::Think() {
CombatSitiation* sit =
GetSituation():
sit->Observe();
for each available action {
if(action.IsApplicable(sit)) {
determine value of action
in sit;
if better than best action,
make best action }
execute best action();
void SoloAI::Think() {
CombatSitiation* sit =
GetSituation():
sit->Observe();
sit->ProcessTeamIntentions();
sit->ProcessTeamObservations();
for each available action {
if(action.IsApplicable(sit)) {
determine value of action
in sit;
if better than best action,
make best action }
nearbySqdMembers->AnnounceAction();
execute best action();

40. Squad Tactics: Solo AI vs Squad Member
Fire-and-maneuver behavior
If too many static squad members, move up
If too many engaging threat, won't stop to engage same threat
Robust against squad member casualties
Interactions easily translated to audio for effect/realism

41. Squad Tactics: Squad Assault
Tactical behavior (on top of fire/move)
Stay close to cover
Don't block other's line-of-fire
Take weapon ability into account
Maintain team cohesion / line-of-sight
Spread out to avoid being a single target
Keep a line-of-sight on enemy

42. Squad Tactics: Squad Assault – Squad Members Mental Picture
For each squad member
Current pos and activity
Claimed destination
Line-of-fire
For each opponent
Last known position and state
Estimated position
Squad members engaging this opponent
For other threats (grenades, fires)
Known/estimated position
Damage radius

43. Squad Tactics: Squad Assault with Four-Man Patrol in Hostile Situation

44. Squad Tactics: Leader evaluating positions and picking one (center, top)

45. Squad Tactics: Executing L-Shaped Ambush
Wait until enemy enters kill zone, aggressively attack, pull back to predefined rally point
Problems
Decentralized squad has trouble waiting until right moment to attack. Attack moment requires some kind of coordination
Squad lacks autonomy
Can't create L-shape itself, can't abort if enemy doesn't show up

46. Squad Tactics: Decentralized Squad (reference)

47. Squad Tactics: Relation Between Squad and Squad Member

48. Squad Tactics: Centralized Approach
Advantages
Separates concerns – reduces number of problems each AI has to deal with
Saves CPU – do computations once
AIs can be specialized independently from each other

49. Squad Tactics: Centralized Approach
Authoritarian command style
No "I" in "team"
Squad can sacrifice a member to achieve a goal
Squad member's view might conflict with squad's objective
Told to defend a front, but sniper is behind
Coaching command style
Each squad member given tasks
Can choose to ignore and tell squad he can't comply
Deals with sniper case
But squad members get distracted easily

50. Squad Tactics: Situation and Extracted Features
Force ratio 5:3, line-of-fire ratio 2:1

51. Squad Tactics: FSM for Valid Maneuvers
Avoids oscillations
FSM prevents attacking before completing pullback

52. Squad Tactics: Bounding Overwatch Pullback
Tail Squad Member’s Behavior
Teammates lay down suppression fire

53. Squad Tactics: Bounding Overwatch Pullback
Pullback path, Cover fire locations, and two bounding moves in progress

54. Squad Tactics: Stages of Performing a Maneuver

55. Team Member AI: Avoiding Friendly Fire
If player is shooting, how can buddy AI avoid friendly fire?
If player is moving around, how can buddy AI avoid friendly fire?

56. Team Member AI: Avoiding Friendly Fire
Two options

57. Planning

58. Planning
Find series of actions for AI that changes the current configuration of the game world into a target configuration
Planning allows innovative solutions when the game world is sufficiently rich
Requires
Planning algorithm
World representation
Choosing set of actions
Action
Preconditions
Effects

59. Planning

60. Planning Config1: Target not dead Action: Attack
Config2: Target is dead, Weapon must be loaded
Action: Load Weapon
Config3: Target is dead, Weapon loaded, Weapon must be armed
Acton: Draw Weapon
Config4: Target is dead, Weapon is loaded, Weapon is armed