Search and planning

Search and planning means exploring possible actions or solutions in a structured way—like choosing a route—rather than guessing one answer in a single breath.

Games, robotics, scheduling, and many agent loops use planning ideas. Even chat assistants sometimes “search” among draft plans before answering.

You define:

• a state (where you are)
• actions (legal moves)
• a goal (what “done” means)
• sometimes a cost (time, money, risk)

Algorithms explore options: try nearest first, best-looking first, or random samples—depending on the problem size.

Planning errands: store A then B vs B then A—pick the shorter total drive. That is search over sequences.

Write a tiny plan for “publish a blog post” with 5 steps. Mark which steps need a human approval gate.

⚠️ Myth: Bigger models make planning unnecessary.

✓ Reality: Models still benefit from explicit steps, tools, and constraints.

⚠️ Myth: The first plan is usually optimal.

✓ Reality: Early plans are drafts; revise with new information.

• Russell & Norvig, *Artificial Intelligence: A Modern Approach* (classic framing; cite edition you own)
• fast.ai practical ML mindset: https://www.fast.ai/ ↗
• ANN Learn agents cluster cross-links