Pathdinding algorithms are instrumental to games developement and devlopers having an ever changing world is just as important so i compared various guided and non-guided algorithms against Dstar lite to show developers the which one may be best suited for the game which they may be developing
Each of the chosen pathfinding algorithms were devloped in SFML using C++ as the coding language They were run on a 2D Grid of Cells/Node which all hold their own information the grid can change sizes ranging from a 10x10 grid to a 100x100 sized grid. The User is free to place down as many walls on the grid as they so wish,they can then run the algorithm which they choose on the grid.The algorithms available are Astar search algorithm, Dijkstras search algorithm, Dstar Lite search algorithm, Lifelong Planning Astar search algorithm, Jump Point search pathfinding algorithm and Depth first Search pathfinding algorithm. The User can then select whether they want to see the algorithm of their choice run against Dstar lite which is run on a seperate screen using the same start and endpoints which they choose. They also have the option to run Dstar Lite in debug mode which will show all of the variable changes which Dstar Lite causes on the grid.
With the results gathered as a part of this research project, under the context of computer games developement it does not show any benefits to use Dstar lite, as in computer games developement it is not common to how massive grid sizes to the point where the benefits of Dstar Lite are far greater than the other search algorithms such as Astar for example.Also Astar is far easier to implement with less memory overhead on smaller grids so this is why i found using the data collected that Dstar lite under a games context is not as applicable as the other search algorithms
If i were to continue my work i would add more search algorithms to compare against Dstar lite from "focused Dstar", "Dstar", "IDA star" and against more non-guided search algorithms "such as breadth first search" with these algorithms being compared against Dstar Lite it would further help developers in making an informed decision on the benefits of Dstar Lite against other guided and non-guided search algorithms as well as prehaps its drawbacks