The AI’s Playbook: Search Strategies Explained (03.1) скачать в хорошем качестве

The AI’s Playbook: Search Strategies Explained (03.1)

This lesson breaks down how AI solves complex problems through search—from defining the puzzle to exploring paths and avoiding infinite loops. You’ll learn how AI agents use structure, memory, and strategy to navigate massive state spaces, and how DFS, BFS, and UCS each bring unique strengths to the table. 🔹 🧩 How to define a search problem: state space, successors, start state, goal test 🔹 📍 The difference between the state graph (the map) and the search tree (the journey) 🔹 🔁 Explored sets that prevent loops and wasted work 🔹 ⚡ Depth-First Search: the deep-diving, memory-efficient explorer 🔹 🌊 Breadth-First Search: the layer-by-layer, complete and optimal (when costs match) method 🔹 🏷️ Uniform Cost Search: expanding the lowest-cost path using a priority queue 🔹 ⚖️ Trade-offs: optimality, completeness, memory, and problem fit 🔹 🚗 Applying search to real maps, puzzles, routing, and planning tasks 🔹 🧭 The stage set for informed search—using hints to guide the agent toward the goal 👉 Next video:    • AI’s Quest: Finding the Path Through Searc...   AI’s Quest: Finding the Path Through Search (03.2) 👉 Previous video:   • A Maze Runner’s Guide to AI: How Search Re...   A Maze Runner’s Guide to AI: How Search Really Works (03.0) 📚 Playlist:    • Introduction to Artificial Intelligence 🤖f...   Introduction to Artificial Intelligence for Software Engineers Happy learning with SmartCode Learning.    / @smartcodelearning