stem/AI/Searching/Informed.md

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# Best First
- Uniform cost uses an evaluation function
- Doesn't necessarily direct towards goal
- Doesn't know how far to goal
- Only cost so far
- Still blind
- Look forward
- Lot of techniques aiming to define best node
1. Expand node closest to goal
- Greedy
2. Expand node on least cost solution path
- A*
# Greedy
- **Estimate** distance to goal
- Often can't determine exactly
- This cost is a heuristic
- Could be crow-flies distance
- Expand nodes in increasing order of heuristic cost
- **Fast**
- **Not optimal**
- Simple heuristic
# A*
- Combines advantages of uniform cost and greedy search
- ***Optimal & Complete***
- $h(n)$
- Estimate of distance to goal
- Greedy
- $g(n)$
- Cost of cumulative path
- *Uniform cost*
- $f(n)=g(n)+h(n)$
- Heuristic must be ***admissible***
- Underestimates the distance to the goal
- Never overestimates
- Monotonic
- Expand other low cost paths
- Pathmax
- For heuristics which might not be monotonic
- Select last option if going in wrong direction