I am working on an online course on AI and I am now working to understand A* better.Basically, right now I am working on a problem where: we live on a tropical island and we're trying to navigate between areas, starting from d and heading towards q.I am trying to find:the cost used between d and q using A* searchhow many 'nodes' that were opened during the searchWhether this route is actually optimalHow many cycles where detectedIf the person was good at swimming, and what could we change the value of q-r (that's the river path) from 240 to what, to lead to the optimal path.(see far below for my ideas to these problems)Below is the costs (when travelling to nodes)Below is the distance to the targetAttempt at SolvingThe optimal path from d to q is d->e->f->g->l->n->q with which would give me a cost of 50+70+20+60+45+20 = 265. This looks like it is the optimal path to get from d to q as well.Also, we should be expanding 1+2+2+3+1+1=10 nodes to find this path with A*.I tried a bunch of other different paths and it looks like this one gives us the least cost. So YES! this is true.Err, this one I don't actually know how to do. Is there a cycle detector in A*?If the cost of q-r was 0, then that would be the best route indeed. (This seems pretty obvious).Can any of you AI gurus/graph theorists help me confirm whether I am understanding this properly?Thanks a ton in advance!
Understanding A* Search on Tropical Island
graph theory;graphs;artificial intelligence;search algorithms