TY - JOUR A2 - Wong, Kok Wai AU - John, Tng C. H. AU - Prakash, Edmond C. AU - Chaudhari, Narendra S. PY - 2008 DA - 2008/04/08 TI - Strategic Team AI Path Plans: Probabilistic Pathfinding SP - 834616 VL - 2008 AB - This paper proposes a novel method to generate strategic team AI pathfinding plans for computer games and simulations using probabilistic pathfinding. This method is inspired by genetic algorithms (Russell and Norvig, 2002), in that, a fitness function is used to test the quality of the path plans. The method generates high-quality path plans by eliminating the low-quality ones. The path plans are generated by probabilistic pathfinding, and the elimination is done by a fitness test of the path plans. This path plan generation method has the ability to generate variation or different high-quality paths, which is desired for games to increase replay values. This work is an extension of our earlier work on team AI: probabilistic pathfinding (John et al., 2006). We explore ways to combine probabilistic pathfinding and genetic algorithm to create a new method to generate strategic team AI pathfinding plans. SN - 1687-7047 UR - https://doi.org/10.1155/2008/834616 DO - 10.1155/2008/834616 JF - International Journal of Computer Games Technology PB - Hindawi Publishing Corporation KW - ER -