Uniform-Cost Search

Definition:​

Uniform-Cost Search (UCS) is a search algorithm that expands the node with the lowest cost first, ensuring that it finds the least-cost path in weighted graphs. UCS is similar to Dijkstra's algorithm but is often applied in AI and pathfinding scenarios.

Video Explanation**​

Watch

Characteristics:​

• Lowest Cost Path: Always expands the node with the lowest path cost.
• Optimal: Guarantees an optimal solution for paths with non-negative weights.
• Uninformed: Does not use heuristics and is a type of uninformed search.

How Uniform-Cost Search Works:​

1. Initialize: Start with the root node.
2. Expand Node: Choose the node with the lowest cumulative path cost.
3. Add Neighbors: Add unvisited neighbors with updated path costs.
4. Repeat: Continue until reaching the goal or emptying the priority queue.

Time Complexity:​

• Time Complexity: (O(b^d)) where b is the branching factor and d is the depth of the goal.

Space Complexity:​

• Space Complexity: (O(b^d))

Advantages of Uniform-Cost Search:​

• Optimal Path: Finds the least-cost path for weighted graphs.
• No Heuristic Needed: Effective without heuristic guidance.

Disadvantages of Uniform-Cost Search:​

• Inefficient for Large Graphs: Can be slow for large search spaces.
• High Memory Use: Stores all frontier nodes in memory.

Uniform-Cost Search Algorithm (Java Implementation):​

import java.util.*;

class GraphNode {
    int id, cost;
    List<GraphNode> neighbors;

    GraphNode(int id, int cost) {
        this.id = id;
        this.cost = cost;
        neighbors = new ArrayList<>();
    }
}

class UniformCostSearch {
    public static int ucs(GraphNode start, GraphNode goal) {
        PriorityQueue<GraphNode> pq = new PriorityQueue<>(Comparator.comparingInt(n -> n.cost));
        Set<GraphNode> visited = new HashSet<>();
        pq.add(new GraphNode(start.id, 0));

        while (!pq.isEmpty()) {
            GraphNode current = pq.poll();
            if (current.id == goal.id) return current.cost;
            visited.add(current);

            for (GraphNode neighbor : current.neighbors) {
                if (!visited.contains(neighbor)) {
                    pq.add(new GraphNode(neighbor.id, current.cost + neighbor.cost));
                }
            }
        }
        return -1; // Goal not reachable
    }
}

Applications of Uniform-Cost Search:​

Pathfinding in AI: Used for finding the shortest path in robotics. Network Routing: Ensures the lowest cost route in weighted networks. Resource Allocation: Finds optimal paths with resource constraints.

Summary:​

Uniform-Cost Search is optimal and complete for finding the lowest-cost path in weighted graphs, widely used in AI and networking.