Hi guys, I am currently working on my dissertation artefact, which involves developing and implementing a pathfinding algorithm that is both cooperative and able to handle dynamic environments. Now my thought process so far has been to find a) a "easy" to implement cooperative A* algorithm (in this case CA*) and b) a "easy" to implement dynamic pathfinding algorithm (in this case D* lite) and hit them with a hammer until they play nice... thus producing an (inelegant and not particularly optimised) implementation that works. I am aware that my choice of method and algorithms (especially CA*) are not perfect, and it pains me to not take my time making a pure algorithm of my own, but the objective of the dissertation is to create an algorithm that when a human is shown two images of paths (one human path and one algorithm-generated path) they cannot reliably discern which is created by the AI, hence the reason I am not too bothered about speed and optimisation. Also, the dissertation artefact demo is only a few weeks away :(, so I cannot dawdle too much. My problem is thus, I have managed to get the algorithm mostly completed but I am struggling to finish this off, mostly due to the fact that CA* uses a 3-dimensional reservation table that doesn't slot in well with other algorithms. I have been trying to find more than just research papers to get information from, but have not had much luck. Is anyone here aware of any sites or books with articles or sections on either of these algorithms? Source code would be nice, but if it was helpful, I would end up re-writing half of it anyway, so I am not fussed if there is any or not, since the workload would essentially be the same. I would have no qualms ditching CA* and re-writing with another co-operative algorithm, but to do so, I would need a written step-by-step description of the algorithm to aid my work, which has so far proven elusive, or crashed my browser when I try to open a paper of interest :(. Any help would be appreciated, and I apologise if I missed any important information out, I managed to catch a bit of a man-cold today and I'm not quite with it.