informed and uninformed search in artificial intelligence

about artificial intelligence

1. Informed and Uninformed Search in AI This presentation explores the fundamentals of search algorithms in AI, focusing on the differences between informed and uninformed strategies. We'll delve into various algorithms, highlighting their strengths and limitations. Dhruv Jain CSE/22/110

2. Introduction to Search Algorithms Core of Problem-Solving Search algorithms are central to AI systems, providing a structured method to find solutions in complex spaces. Navigating the Solution Space These algorithms systematically explore potential solutions, searching for the optimal path to a goal.

3. Uninformed Search Strategies 1 Blind Exploration These strategies lack knowledge of the solution space and rely on general rules. 2 Equal Treatment They consider all potential solutions equally, without favoring any particular path.

4. Breadth-First Search (BFS) Layer-by-Layer Expands outwards level by level, exploring all nodes at a given depth before moving to the next. Complete and Optimal Guarantees finding the shortest path if one exists, but can be inefficient for large spaces.

5. Depth-First Search (DFS) Branch-by-Branch Explores one branch fully before backtracking and exploring other branches. Suitable for Deep Spaces Efficient for finding solutions quickly, but may not find the optimal path.

6. Informed Search Strategies Heuristic Guidance These strategies leverage domain knowledge to make informed decisions. Prioritized Exploration They prioritize promising paths based on an estimated distance to the goal.

7. Heuristic Functions and A* Search Heuristic Guidance Uses a heuristic function to estimate the distance to the goal. 1 Cost and Heuristic A* combines path cost with the heuristic estimate to make informed decisions. 2 Optimal Path Guarantees finding the optimal path if the heuristic is admissible. 3

8. Greedy Best-First Search 1 Shortest Heuristic Expands the node with the lowest heuristic value, prioritizing immediate progress. 2 Not Guaranteed Optimal May find a solution quickly but not necessarily the best one.

9. Conclusion and Key Takeaways Uninformed vs. Informed Uninformed searches are blind, while informed ones use domain knowledge. A* Search A* combines path cost and heuristic estimation to find optimal paths. Greedy Best-First Prioritizes immediate progress, but may not find the best solution.