Heuristics: intelligent search strategies for computer problem solving
Heuristics: intelligent search strategies for computer problem solving
Depth-first iterative-deepening: an optimal admissible tree search
Artificial Intelligence
Time complexity of iterative-deepening-A
Artificial Intelligence - Special issue on heuristic search in artificial intelligence
Human-Level AI's Killer Application: Interactive Computer Games
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Theta*: any-angle path planning on grids
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Comparison of different grid abstractions for pathfinding on maps
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Journal of Intelligent and Robotic Systems
Theta*: any-angle path planning on grids
Journal of Artificial Intelligence Research
Graph pruning and symmetry breaking on grid maps
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
BA*: an online complete coverage algorithm for cleaning robots
Applied Intelligence
Hi-index | 0.00 |
Path-finding is an important problem for many applications, including network traffic, robot planning, military simulations, and computer games. Typically, a grid is superimposed over a region, and a graph search is used to find the optimal (minimal cost) path. The most common scenario is to use a grid of tiles and to search using A*. This paper discusses the tradeoffs for different grid representations and grid search algorithms. Grid representations discussed are 4-way tiles, 8-way tiles, and hexes. This paper introduces texes as an efficient representation of hexes. The search algorithms used are A* and iterative deepening A* (IDA*). Application-dependent properties dictate which grid representation and search algorithm will yield the best results.