Qualitative Spatial Analysis

1. Qualitative Spatial Analysis Chris Mansley

2. Qualitative • Quantitative items are known, definable quantities • (x,y) coordinates • Remaining health • Location of units • Qualitative items are much more intangible but intimately related to qualitative items • By decoupling the two, more general code/ideas can be used about the AI

3. An example • Trafficablity • Given a map and an echelon • Restricted (Impassible) • Restricted (Passable) • Unrestricted • Mobility Corridors • Avenues of Approach

4. Example (cont.)

6. Motivations • Game worlds are increasingly more complex • NPC must be able to reason about them in an intelligent fashion • Dynamic environments • Makes scripting less of an option • Leads to more problems

7. Two Implementations • Spatial Database • Driven by the dynamic environments associated with FPS • Terrain Analysis • Needed a realistic way to analyze strategic value in RTS

8. Conventional Methods • Conventional Spatial Ideas • NPCs are guided by “hints” placed in the level by designers • Offline analysis of level to build a data structure the NPCs can use to interact with the environment

9. AI Nodes

10. Conventional Methods (cont.) • Flaws • Only works for static environments! • May be difficult with random maps

11. Spatial Databases • 2-D Grid overlaid on the game world • Each cell can have many layers of data • Can be thought of as several grids laid on top of one another

12. Spatial Databases Openness layer Occupancy layer Search layer

13. Data Layers • Openness Layer (Static) • Cover Layer (Static) • Area Search Layer (Dynamic) • Area Occupancy Layer (Dynamic) • Line-of-Fire Layer (Dynamic) • Light Level Layer (Dynamic)

14. Using Layers • Layers can be combine to form desirability layers for different scenarios • Combat Desirability • Openness • Occupancy • Cover

15. Using Layers (cont.) • Benefits • Implicitly coordinate multiple AI units • Generate multiple movements for different actions

16. Using Layers (cont.) • Drawbacks • Does not handle 3-D environments easily • Simple Solution – break 3-D environment into smaller grids • Potentially processor intensive • Streamline resolution of grid to get best possible results

17. Calculating Desirability Openness layer Occupancy layer 0.6 0.6 0.6 1 0.6 0.8 0.8 Cover layer 1 0.8 0.6 1 0.8 Desirability layer 1 0.6 0.6 0.6 = 0 0 0 0.6 0 0 0.6 0 0 0 0 0

18. Openness Layer • A cell containing a wall or blocking object contains a zero • All other cells contain a one • The zero is propagated to neighboring cells to be able to determine proximity to the wall

19. Openness Layer (cont.) Solid Wall

20. Area Occupancy Layer • Similar to fog-of-war feature from RTS • Nonzero values are placed where the unit is located • That value is propagated to the neighboring cells

21. Area Occupancy Layer (cont.)

22. Line-of-Fire Layer • Useful with ranged weapons • Helps AI avoid shooting each other • Has a nonzero value in each cell in the direction of fire

23. Line-of-Fire (cont.)

24. Light Level • Dynamic lighting is an important part of modern games • Visibility/area lighting can be taken into account by NPCs • The layer has the light intensity at any cell

25. Area Search Layer • In many “sneaker” games, the NPCs spend time searching for the player • Once searched, the area layer contains true or some nonzero value • Over time that layer can decay, so the NPC will research it if necessary

26. Thief: Deadly Shadows

27. References • AI Game Programming Wisdom 2 • Forbus, K., “How Qualitative Spatial Reasoning Can Improve Strategy Game AIs”, IEEE Intelligent Systems, July/August 2002 • Thief: Deadly Shadows, Ion Storm/Eidos Interactive 2004