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AI · Theory

Iterative Deepening A* Algorithm (IDA*)

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Theory

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Iterative Deepening A* Algorithm (IDA*)

Iterative Deepening A* Algorithm (IDA*) is a search strategy. Say the data structure, whether it uses a heuristic, and if it guarantees a shortest path. Draw a tiny 6-node graph. That is the exam, not a textbook proof.

Iterative Deepening A* Algorithm (IDA*) — output: three exam lines. Graph on paper first.

For Iterative Deepening A* Algorithm (IDA*): always mark visited nodes or you loop. Say complexity in plain words: time vs memory trade-off.

Diagram
f(n) = g(n) + h(n)
  pick smallest f
  admissible h → optimal
Exam tip

DS + heuristic yes/no + optimality.

Example

# Iterative Deepening A* Algorithm (IDA*)
print("draw 6 nodes")
print("name the DS: queue / stack / priority")
print("say if the path is optimal")

Iterative Deepening A* Algorithm (IDA*) — output: three exam lines. Graph on paper first.

Short notes

  • DefIterative Deepening A* Algorithm (IDA*) — how we walk the state graph.
  • RuleIterative Deepening A* Algorithm (IDA*) — visited set.
  • RememberIterative Deepening A* Algorithm (IDA*) — heuristic or not?

Questions

1

Explain Iterative Deepening A* Algorithm (IDA*) as if you are teaching a junior — definition, then one example.

2

What does the example print, and what does that prove?

3

What mistake do freshers make with Iterative Deepening A* Algorithm (IDA*)?

Previous← Chatbot vs. Conversational AINextIterative Deepening Search (IDS) or Iterative Deepening Depth First Search (IDDFS) →
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