Added A* algorithm !

tutorials/Grid World/a_star.py

@@ -0,0 +1,65 @@
+from traverseCraft.world import CreateGridWorld
+from traverseCraft.agent import GridAgent
+
+gridWorld = CreateGridWorld(worldName="Simple Grid World", cols=7, rows=7, cellSize=36)
+gridWorld.constructWorld()
+
+gridWorld.setBlockPath(blockCells=[[1,1],[2,2],[3,3],[4,3]])
+
+gridAgent = GridAgent(agentName="Simple Grid Agent", world=gridWorld, agentPos=[0,0])
+gridWorld.setAgent(agent=gridAgent)
+
+def heuristic(pos, goal):
+    # Manhattan distance heuristic
+    return abs(pos[0] - goal[0]) + abs(pos[1] - goal[1])
+
+def astar(agent, start, goal):
+    open_list = [(0, start)]
+    came_from = {}
+    g_score = {start: 0}
+
+    while open_list:
+        open_list.sort()
+        current = open_list.pop(0)[1]
+
+        if current == goal:
+            path = []
+            while current in came_from:
+                path.append(current)
+                current = came_from[current]
+            path.append(start)
+            path.reverse()
+            return path
+
+        for di, dj in [(-1, 0), (1, 0), (0, -1), (0, 1)]:
+            ni, nj = current[0] + di, current[1] + dj
+            if 0 <= ni < 7 and 0 <= nj < 7 and not agent.checkBlockState(ni, nj):
+                tentative_g_score = g_score[current] + 1
+                if (ni, nj) not in g_score or tentative_g_score < g_score[(ni, nj)]:
+                    came_from[(ni, nj)] = current
+                    g_score[(ni, nj)] = tentative_g_score
+                    f_score = tentative_g_score + heuristic((ni, nj), goal)
+                    open_list.append((f_score, (ni, nj)))
+
+    return None
+
+def toDo():
+    start = (0, 0)
+    goal = (6, 6)
+
+    path = astar(gridAgent, start, goal)
+
+    if path:
+        print("Found path:", path)
+        for pos in path[1:]:
+            gridAgent.moveAgent(pos[0], pos[1])
+            print("Agent moved to:", pos)
+        print("Agent reached the goal state!")
+    else:
+        print("No path found. Agent could not reach the goal state!")
+
+gridAgent.setAlgorithmCallBack(toDo)
+gridWorld.showWorld()
+
+print(gridWorld.summary())
+print(gridAgent.summary())