Modifying Dijkstra's Algorithm to an A* implementation - c

Question

I'm in the process of creating a maze simulation of a mouse running through a maze. Dijkstra's algorithm is great and all but isn't particularly effected when cats are involved, which is why I'm trying to modify my existing Dijkstra implementation to an A* search with a heuristic for avoiding the cats which move throughout the maze.
The problem I'm having while I look through some pseudocode is I am unsure of what structures are equivalent or what will I need to introduce to get this working. Can anyone provide any tips or nudges in the right direction?
struct path_node *shortestPath(float A[GsizeSqr][GsizeSqr], int xi, int yi, int xf, int yf)
{
/*
Solves for the shortest path between grid point (xi,yi) and (xf,yf)
on the graph encoded by A using Dijkstra's shortest path method.
The shortest path is returned as a linked list of nodes to be visited.
Keep track of visited nodes, and the predecessor
for each node that has been explored while computing the shortest path.*/
if (xi<0||xi>=Gsize&&yi<0&&yi>=Gsize||xf<0||xf>=Gsize||yf<0||yf>=Gsize)
{
fprintf(stderr,"shortestPath(): Endpoint(s) outside of the graph!\n");
return(NULL);
}
int i, j, pCount, findN, row, col, icnt, stNode, finNode, xcnt, ycnt;
finNode = yf * ceil(sqrt(GsizeSqr)) + xf; //index of start node given its row and col value
stNode = yi * ceil(sqrt(GsizeSqr)) + xi; //index of finish node given its row and col value
int p[GsizeSqr]; //predecessors
int d[GsizeSqr]; //distance from source
int flags[GsizeSqr]; //(0, 1) for unvisited, visited)
int g_score[GsizeSqr];
int f_score[GsizeSqr];
PriorityQueue Q; //Initialize priority queue that stores (priority, key) values
Q = init_heap(GsizeSqr);
path_node *start; //Maintain a pointer to the starting node
start = newPathNode(xi, yi);
start->next = NULL;
//Initialize p and d with infinity and NULL values (note: -1 means null and 1000000 means inf)
for(i=0; i < GsizeSqr; i++){
p[i] = -1;
d[i] = 10000000;
flags[i] = 0;
}
for(i=0; i < GsizeSqr; i++){
node in;
in = create_node(10000000, i);
enqueue(Q, in);
}
//(Note: PQ uses 0 as a sentinel node to make calculating left, right, and parents easier, elements begin at 1)
decrease_priority(Q, stNode+1, 0); //setting start node in PQ.
d[stNode] = 0;
g_score[stNode] = 0;
//For my heuristic, I'm thinking just using manhattan distances between mouse and cat agents
f_score[stNode] = g_score[stNode] + heuristic(xi, yi, xf, yf);
while(Q->heap_size != 1){ //while Q not empty
node u;
u = dequeue(Q);
flags[u.key] = 1;
//For each adjacent node A[u.key][i]
for(i=0; i < GsizeSqr; i++){
if(A[u.key][i] != 0){
findN = find_node(Q, i);
if(flags[i] == 0){ //If it is unvisited and new path distance is shorter
if(findN != 0 && (d[i] >= A[u.key][i] + d[u.key])){ //reset values and update PQ and mark visited
d[i] = A[u.key][i] + d[u.key];
p[i] = u.key;
flags[i] = 1;
decrease_priority(Q, findN, d[i]);
}
}
}
}
}
// Begin selectively filling our LL with values from p[]
icnt = finNode;
appendLL(start, xf, yf);
while(icnt != stNode){
icnt = p[icnt];
xcnt = icnt % (int)ceil(sqrt(GsizeSqr));
ycnt = icnt / (int)ceil(sqrt(GsizeSqr));
appendLL(start, xcnt, ycnt);
}
clean_heap(Q);
return reverseLL(start);
}

Answer 1

You possibly already know this, but the only theoretical difference between A* and Dijkstra's algorithm in terms of best-first search is the cost function f(n). Dijkstra's algorithm is f(n) = g(n) whilst A* is f(n) = g(n) + h(n). Read AIMA for details.
In terms of your code, it currently stores g(n) = A[u.key][i] + d[u.key] in d[i], so you need to change it store g(n) + h(n). You don't need those new g_score and f_score variables, just add the heuristic to the end of that line and the initialization of d[stNode].