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Hi Thomas,
good to see yet another AI IOTD. It looks good. I suppose this corresponds to your AI Programming Wisdom chapter?
This would be attractive AI path-finding middleware to me when:
- the effort involved in developing/nicking something similar myself is less than the duration of the contract negotiation (which easily takes 1 month);
- it would offer, behind a narrow interface, a wide range of pathfinding algorithms, so I have the flexibility to use and swap:
--- pre-computed path tables (in a few variants, trading path retrieval time for memory consumption)
--- hierarchichal on-the-fly pathfinding
--- on-the-fly (A*) pathfinding with per NPC path caching policies
--- efficient multi-path pathfinding (so an NPC picks one of multiple 'good enough' paths to a destination, reducing its (artificial) predictability);
--- pathfinding optimized to large open terrain or indoors
--- take into account various movement constraints (accumulating falling damage, rocket jumps, ...)
--- take into account dynamic obstacles (often, proximity checks during movement and replanning is cheaper than trying to predict all exceptions the future might bring);
- it would provide as free downloads sample code and impressive benchmarks, so I have a chance at convincing my producer.
Think of C++'s STL: one interface to containers, and the ability to swap container implementation without much fuss.
There seems to be an interesting contrast between your experience "[...] a load of games that could all have used the same pathfinding system [...]" and mine (tactical fps AI):
in my case, a single game typically has multiple pathfinding algorithms (although all based on waypoints), in order to get the best performance for short paths, path length comparisons, squad level pathfinding and tactical pathfinding.
I'm looking forward any additional info you will provide on your site.
William
p.s. on your pathfinding.htm, 3rd bullet underneath "what can you do with pathfinding", the sentence looks garbled.
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