c - ダイクストラのアルゴリズムを A* 実装に変更する

Question

迷路を走るマウスの迷路シミュレーションを作成中です。Dijkstra のアルゴリズムは優れていますが、猫が関係している場合は特に影響を受けません。そのため、既存の Dijkstra の実装を、迷路全体を移動する猫を回避するためのヒューリスティックを使用して A* 検索に変更しようとしています。

疑似コードを調べているときに私が抱えている問題は、どの構造が同等であるか、またはこれを機能させるために何を導入する必要があるかがわからないことです。誰でも正しい方向へのヒントやナッジを提供できますか?

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);
}