Скачать или смотреть CST 351 Lesson 4: Types of AI search - strategies and evaluation of search performance

Search Techniques II - Types of AI search strategies and
evaluation of search performance

CST 351: Search Techniques II** explores core AI search strategies and compares their performance. Building on foundational concepts like state spaces and combinatorial explosion, the lecture introduces more advanced search methods.

Topics include:

Uninformed (Blind) Search: Breadth-First Search (BFS) and Depth-First Search (DFS), which explore the problem space without domain knowledge.
Informed (Heuristic) Search: Greedy Best-First Search and A*, which use heuristics to guide exploration more efficiently.

Key takeaways:

BFS:Complete and optimal for equal step costs.
DFS:Memory-efficient but neither complete nor optimal.
Greedy Best-First Search:Chooses nodes closest to the goal based on a heuristic.
A* Search: Balances path cost and heuristic estimates for optimal, efficient search.

The lecture concludes with a Universal Search Blueprint and simple Python examples showing how each algorithm manages its search frontier.