Lec # 1: Best First Search | Informed Searching | Artificial Intelligence | Full Detail скачать в хорошем качестве

Lec # 1: Best First Search | Informed Searching | Artificial Intelligence | Full Detail

Abdul Hanan AI Algorithms notes: https://drive.google.com/drive/folder... #artificialintelligence #artificial #intelligence #algorithms #best #first #search #Information #technology #computer #science #TECH #STUDY The Best First Search algorithm is a popular search technique used in Artificial Intelligence (AI) to solve problems by exploring a search space. It is an informed search algorithm, meaning it uses heuristic information to guide the search process, making it more efficient compared to uninformed search algorithms like Breadth-First Search (BFS) or Depth-First Search (DFS). How Does Best First Search Work? Heuristic Function: Best First Search uses a heuristic function to estimate how close a given state (or node) is to the goal. The heuristic function, denoted as h(n), provides an approximate cost or distance from the current node to the goal. Example: In a pathfinding problem, the heuristic could be the straight-line distance (Euclidean distance) from the current node to the goal. Priority Queue: The algorithm maintains a priority queue (often implemented using a heap) to store nodes. Nodes are prioritized based on their heuristic value. The node with the lowest heuristic value (i.e., the most promising node) is explored first. Exploration Process: Start from the initial node and add it to the priority queue. Repeatedly select the most promising node (lowest heuristic value) from the queue, expand it, and add its successors to the queue. If the goal node is reached, the algorithm terminates.