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 Search layer Occupancy layer Openness 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 Cover layer Occupancy layer Openness layer 1 0.6 0 Desirability layer 0 1 0.8 1 0.6 00 1 00 00 00 =

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