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Gravit Certificate:
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  • 1.1 The A* Search Algorithm & Admissibility
  • 1.2 Manhattan Distance Heuristic in Grid Worlds
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Module 1: Informed State Space Search & A*•Lesson 1

1.1 The A* Search Algorithm & Admissibility

### The A* Evaluation Function
A* explores nodes by evaluating:
$$f(n) = g(n) + h(n)$$
* **$g(n)$:** The exact cost accumulated from the start node to current node $n$.
* **$h(n)$:** The estimated heuristic cost from node $n$ to the goal.

An admissible heuristic **never overestimates** the true cost to reach the goal ($h(n) \le h^*(n)$), guaranteeing A* finds the optimal shortest path.
Python 3.11
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Interactive Challenge
+100 XP
Challenge Objective

Compute the A* evaluation cost and output 'F_COST: 25'.

solution.py
UTF-84 SpacesAuto-saved
cpython3.11:~/workspace
CPython 3.11.8 (WASM)
$python3 -u solution.py
Click "Compile & Run" (or press Ctrl + Enter) to compile AST, verify bytecode, and execute the solution.