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Proof-number search

Proof-number search is a mathematics topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Proof-number search rather than just read about it. In short: Proof-number search (short: PN search) is a game tree search algorithm invented by Victor Allis, with applications mostly in endgame solvers, but also for sub-goals during games. Using a binary goal (e.g. first player wins the game), game trees of two-person perfect-information games can be mapped to an and–or tree.

Key takeaways

  • Proof-number search belongs to mathematics; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Proof-number search to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Proof-number search from memory before moving on to harder problems.

Reference excerpt

Proof-number search (short: PN search) is a game tree search algorithm invented by Victor Allis, with applications mostly in endgame solvers, but also for sub-goals during games. Using a binary goal (e.g. first player wins the game), game trees of two-person perfect-information games can be mapped to an and–or tree. Maximizing nodes become OR-nodes, minimizing nodes are mapped to AND-nodes. For all nodes proof and disproof numbers are stored, and updated during the search. To each node of the partially expanded game tree the proof number and disproof number are associated. A proof number represents the minimum number of leaf nodes which have to be proved in order to prove the node. Analogously, a disproof number represents the minimum number of leaves which have to be disproved in order to disprove the node. Because the goal of the tree is to prove a forced win, winning nodes are regarded as proved. Therefore, they have proof number 0 and disproof number ∞. Lost or drawn nodes are regarded as disproved. They have proof number ∞ and disproof number 0. Unknown leaf nodes have a proof and disproof number of unity. The proof number of an internal AND node is equal to the sum of its children's proof numbers, since to prove an AND node all the children have to be proved. The disproof number of an AND node is equal to the minimum of its children's disproof numbers. The disproof number of an internal OR node is equal to the sum of its children's disproof numbers, since to disprove an OR node all the children have to be disproved. Its proof number is equal to the minimum of its children's proof numbers. The procedure of selecting the most-proving node to expand is the following. We start at the root. Then, at each OR node the child with the lowest proof number is selected as successor, and at each AND node the child with the lowest disproof number is selected as successor. Finally, when a leaf node is reached, it is expanded and its children are evaluated. The proof and disproof numbers represent lower bounds on the number of nodes to be evaluated to prove (or disprove) certain nodes. By always selecting the most proving (disproving) node to expand, an efficient search is generated. Some variants of proof number search like dfPN, PN2, PDS-PN have been developed to address the quite big memory requirements of the algorithm.

References

Further reading A. Kishimoto, M.H.M. Winands, M. Müller, and J-T. Saito (2012) Game-tree search using proof numbers: The first twenty years, ICGA, 35(3):131–156, pdf

Worked examples

Example 1 — a first encounter with Proof-number search

Start with the simplest possible case. Write down what Proof-number search claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In mathematics, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Proof-number search before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Proof-number search ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Proof-number search

In research
Proof-number search appears in mathematics research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Proof-number search in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Proof-number search is common in secondary-school and first-year university syllabi. It links to neighbouring topics Game artificial intelligence, Graph algorithms, Search algorithms, so understanding it makes those chapters shorter.
In everyday life
Look for Proof-number search outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study Proof-number search in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Proof-number search means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Proof-number search out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Proof-number search in simple terms?

Proof-number search (short: PN search) is a game tree search algorithm invented by Victor Allis, with applications mostly in endgame solvers, but also for sub-goals during games. Using a binary goal (e.g. first player wins the game), game trees of two-person perfect-information games can be mapped…

Why does Proof-number search matter?

Because it connects several mathematics ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Proof-number search?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Proof-number search.

Tags

  • Game artificial intelligence
  • Graph algorithms
  • Search algorithms

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