Added all the codes.

Codes/Alternatives/Assignment-A2-Direct.py

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+# Assignment-A2 (A* Algorithm)
+
+"""
+THIS CODE HAS BEEN TESTED AND IS FULLY OPERATIONAL.
+
+Problem Statement: Implement A star Algorithm for any game search problem.
+
+Code from ArtificialIntelligence (SPPU - Third Year - Computer Engineering - Content) repository on KSKA Git: https://git.kska.io/sppu-te-comp-content/ArtificialIntelligence
+"""
+
+# This code directly implements A* algorithm for finding the optimal
+# solution. It is NOT implemented for any game search problem.
+
+# A* implementation for 8 puzzle problem can be found in the "Codes" folder
+# and maze problem solving can be found in the "Alternatives" folder.
+
+# BEGINNING OF CODE
+import heapq
+
+def a_star(graph, start, goal, heuristic):
+    g = {v: float('inf') for v in graph}
+    f = {v: float('inf') for v in graph}
+    parent = {v: None for v in graph}
+
+    g[start] = 0
+    f[start] = heuristic[start]
+
+    open_list = [(f[start], start)]
+
+    while open_list:
+        _, current = heapq.heappop(open_list)
+
+        if current == goal:
+            return reconstruct_path(parent, goal, g[goal])
+
+        for neighbor, weight in graph[current]:
+            tentative_g = g[current] + weight
+            if tentative_g < g[neighbor]:
+                parent[neighbor] = current
+                g[neighbor] = tentative_g
+                f[neighbor] = tentative_g + heuristic[neighbor]
+                heapq.heappush(open_list, (f[neighbor], neighbor))
+
+    return []
+
+def reconstruct_path(parent, goal, cost):
+    path = []
+    while goal:
+        path.append(goal)
+        goal = parent[goal]
+    path.reverse()
+    print("Path cost:", cost)
+    return path
+
+def main():
+    n = int(input("Enter number of vertices: "))
+    print("Enter vertex names (e.g., A B C ...):")
+    vertices = input().split()
+
+    graph = {v: [] for v in vertices}
+
+    m = int(input("Enter number of edges: "))
+    print("Enter edges (format: source destination weight):")
+    for _ in range(m):
+        u, v, w = input().split()
+        w = int(w)
+        graph[u].append((v, w))
+        # graph[v].append((u, w))  # Uncomment for undirected graph
+
+    heuristic = {}
+    print("Enter heuristic values (e.g., A 4 B 2 ...):")
+    for _ in range(n):
+        name, h = input().split()
+        heuristic[name] = int(h)
+
+    start = input("Enter start vertex: ")
+    goal = input("Enter goal vertex: ")
+
+    path = a_star(graph, start, goal, heuristic)
+    if path:
+        print("Optimal path:", ' -> '.join(path))
+    else:
+        print("No path found.")
+
+main()
+# END OF CODE