Generalized best-first search strategies and the optimality of A*
Journal of the ACM (JACM)
Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
Robot Motion Planning
Introduction to Algorithms
Brook for GPUs: stream computing on graphics hardware
ACM SIGGRAPH 2004 Papers
ACM SIGGRAPH 2006 Papers
Planning Algorithms
Interactive navigation of multiple agents in crowded environments
Proceedings of the 2008 symposium on Interactive 3D graphics and games
Hierarchical A *: searching abstraction hierarchies efficiently
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
ACM SIGGRAPH 2009 Courses
The Journal of Supercomputing
Parallel ripple search – scalable and efficient pathfinding for multi-core architectures
MIG'11 Proceedings of the 4th international conference on Motion in Games
Hybrid path planning for massive crowd simulation on the GPU
MIG'11 Proceedings of the 4th international conference on Motion in Games
A task parallel algorithm for finding all-pairs shortest paths using the GPU
International Journal of High Performance Computing and Networking
Multi-core pathfinding with Parallel Ripple Search
Computer Animation and Virtual Worlds
A parallel fipa architecture based on GPU for games and real time simulations
ICEC'12 Proceedings of the 11th international conference on Entertainment Computing
International Journal of High Performance Computing Applications
Multiagent and Grid Systems
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In the past few years the graphics programmable processor (GPU) has evolved into an increasingly convincing computational resource for non graphics applications. The GPU is especially well suited to address problem sets expressed as data parallel computation with the same program executed on many data elements concurrently. In pursuing a scalable navigation planning approach for many thousands of agents in crowded game scenes, developers became more attracted to decomposable movement algorithms that lend to explicit parallelism. Pathfinding is one key computational intelligence action in games that is typified by intense search over sparse graph data structures. This paper describes an efficient GPU implementation of parallel global pathfinding using the CUDA programming environment, and demonstrates GPU performance scale advantage in executing an inherently irregular and divergent algorithm.