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Particle Filters and Simulacra for More Realistic Opponent Tracking
| Author: | Christian Darken & Bradley Anderegg |
| Title: | Particle Filters and Simulacra for More Realistic Opponent Tracking |
| Abstract: | Tracking the possible location of an opponent is a potentially important game AI capability for enabling intelligent hiding from or searching for the opponent. This article provides an introduction to particle filters for this purpose. Particle filters postulate a set of specific coordinates where the opponent might be as opposed to estimating probabilities that the opponent is in particular regions of the level, as is done in the occupancy map technique. By their very nature, particle filters have a very different performance profile from occupancy maps, and thus represent an interesting alternative. We also show how adding a small amount of intelligence to the particles, transforming them to simulacra, can improve the quality of tracking. In Game AI Programming Wisdom 4, Charles River, S. Rabin editor, 2008. |
| Date: | 2008 |
| Url: | N/A (not available) |
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