Knuth's Algorithm X: Difference between revisions

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{{Short description|Algorithm for exact cover problem}}

'''"Algorithm X"''' is the name [[Donald Knuth]] used in his paper "Dancing Links" to refer to "the most obvious trial-and-error approach" for finding all solutions to the [[exact cover]] problem.<ref name="knuth" /> Technically, Algorithm X is a [[Recursion (computer science)|recursive]], [[Nondeterministic algorithm|nondeterministic]], [[depth-first]], [[backtracking]] [[algorithm]]. While Algorithm X is generally useful as a succinct explanation of how the [[exact cover]] problem may be solved, Knuth's intent in presenting it was merely to demonstrate the utility of the [[dancing links]] technique via an efficient implementation he called DLX.<ref name="knuth">{{cite arXiv | author = [[Donald Knuth|Knuth, Donald]] | title = Dancing links | year = 2000 | eprint = cs/0011047 }}</ref>

'''Algorithm X''' is an [[algorithm]] for solving the [[exact cover]] problem. It is a straightforward [[Recursion (computer science)|recursive]], [[Nondeterministic algorithm|nondeterministic]], [[depth-first]], [[backtracking]] algorithm used by [[Donald Knuth]] to demonstrate an efficient implementation called DLX, which uses the [[dancing links]] technique.<ref name="knuth">{{cite arXiv | author = Knuth, Donald | author-link = Donald Knuth | title = Dancing links | year = 2000 | eprint = cs/0011047 }}</ref><ref>{{Cite journal |last=Banerjee |first=Bikramjit |last2=Kraemer |first2=Landon |last3=Lyle |first3=Jeremy |date=2010-07-04 |title=Multi-Agent Plan Recognition: Formalization and Algorithms |url=https://ojs.aaai.org/index.php/AAAI/article/view/7746 |journal=Proceedings of the AAAI Conference on Artificial Intelligence |volume=24 |issue=1 |pages=1059–1064 |doi=10.1609/aaai.v24i1.7746 |issn=2374-3468|doi-access=free }}</ref>

==Algorithm==

The [[exact cover]] problem is represented in Algorithm X usingby aan [[incidence matrix]] ''A'' consisting of 0s and 1s. The goal is to select a subset of the rows sosuch that the digit 1 appears in each column exactly once.

Algorithm X functionsworks as follows:

:{| border="1" cellpadding="5" cellspacing="0"

|

# If the matrix ''A'' has no columns, the current partial solution is a valid solution; terminate successfully.

# Otherwise choose a column ''c'' ([[deterministic algorithm|deterministically]]).

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#: delete column ''j'' from matrix ''A''.

# Repeat this algorithm recursively on the reduced matrix ''A''.

|}

The nondeterministic choice of ''r'' means that the algorithm essentiallyrecurses clones itself intoover independent subalgorithms; each subalgorithm inherits the current matrix ''A'', but reduces it with respect to a different row ''r''.

If column ''c'' is entirely zero, there are no subalgorithms and the process terminates unsuccessfully.

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Any systematic rule for choosing column ''c'' in this procedure will find all solutions, but some rules work much better than others.

To reduce the number of iterations, [[Donald Knuth|Knuth]] suggests that the column-choosing algorithm select a column with the lowestsmallest number of 1s in it.

==Example==

For example, consider the exact cover problem specified by the universe ''U'' = {1, 2, 3, 4, 5, 6, 7} and the collection of sets <math>\mathcal{{mathcal|S}</math>} = {''A'', ''B'', ''C'', ''D'', ''E'', ''F''}, where:

:* ''A'' = {1, 4, 7};

:* ''B'' = {1, 4};

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This problem is represented by the matrix:

:{| class="wikitable"

:{| border="1" cellpadding="5" cellspacing="0"

! !! 1 !! 2 !! 3 !! 4 !! 5 !! 6 !! 7

|-

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Step 2—The lowest number of 1s in any column is two. Column 1 is the first column with two 1s and thus is selected (deterministically):

:{| class="wikitable"

:{| border="1" cellpadding="5" cellspacing="0"

! !! 1 !! 2 !! 3 !! 4 !! 5 !! 6 !! 7

|-

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: Step 5—Row ''A'' has a 1 in columns 1, 4, and 7:

::{| class="wikitable"

::{| border="1" cellpadding="5" cellspacing="0"

! !! <span style="color:blue">1</span> !! 2 !! 3 !! <span style="color:blue">4</span> !! 5 !! 6 !! <span style="color:blue">7</span>

|-

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|}

: Column 1 has a 1 in rows ''A'' and ''B''; column 4 has a 1 in rows ''A'', ''B'', and ''C''; and column 7 has a 1 in rows ''A'', ''C'', ''E'', and ''F''. Thus, rows ''A'', ''B'', ''C'', ''E'', and ''F'' are to be removed and columns 1, 4 and 7 are to be removed:

::{| class="wikitable"

::{| border="1" cellpadding="5" cellspacing="0"

! !! <span style="color:red">1</span> !! 2 !! 3 !! <span style="color:red">4</span> !! 5 !! 6 !! <span style="color:red">7</span>

|-

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: Row ''D'' remains and columns 2, 3, 5, and 6 remain:

::{| class="wikitable"

::{| border="1" cellpadding="5" cellspacing="0"

! !! 2 !! 3 !! 5 !! 6

|-

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: Step 2—The lowest number of 1s in any column is zero and column 2 is the first column with zero 1s:

::{| class="wikitable"

::{| border="1" cellpadding="5" cellspacing="0"

! !! <span style="color:red">2</span> !! 3 !! 5 !! 6

|-

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: Row ''B'' has a 1 in columns 1 and 4:

::{| class="wikitable"

::{| border="1" cellpadding="5" cellspacing="0"

! !! <span style="color:blue">1</span> !! 2 !! 3 !! <span style="color:blue">4</span> !! 5 !! 6 !! 7

|-

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|}

: Column 1 has a 1 in rows ''A'' and ''B''; and column 4 has a 1 in rows ''A'', ''B'', and ''C''. Thus, rows ''A'', ''B'', and ''C'' are to be removed and columns 1 and 4 are to be removed:

::{| class="wikitable"

::{| border="1" cellpadding="5" cellspacing="0"

! !! <span style="color:red">1</span> !! 2 !! 3 !! <span style="color:red">4</span> !! 5 !! 6 !! 7

|-

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: Rows ''D'', ''E'', and ''F'' remain and columns 2, 3, 5, 6, and 7 remain:

::{| class="wikitable"

::{| border="1" cellpadding="5" cellspacing="0"

! !! 2 !! 3 !! 5 !! 6 !! 7

|-

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: Step 2—The lowest number of 1s in any column is one. Column 5 is the first column with one 1 and thus is selected (deterministically):

::{| class="wikitable"

::{| border="1" cellpadding="5" cellspacing="0"

! !! 2 !! 3 !! <span style="color:red">5</span> !! 6 !! 7

|-

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:: Step 5—Row ''D'' has a 1 in columns 3, 5, and 6:

:::{| class="wikitable"

:::{| border="1" cellpadding="5" cellspacing="0"

! !! 2 !! <span style="color:blue">3</span> !! <span style="color:blue">5</span> !! <span style="color:blue">6</span> !! 7

|-

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|}

:: Column 3 has a 1 in rows ''D'' and ''E''; column 5 has a 1 in row ''D''; and column 6 has a 1 in rows ''D'' and ''E''. Thus, rows ''D'' and ''E'' are to be removed and columns 3, 5, and 6 are to be removed:

:::{| class="wikitable"

:::{| border="1" cellpadding="5" cellspacing="0"

! !! 2 !! <span style="color:red">3</span> !! <span style="color:red">5</span> !! <span style="color:red">6</span> !! 7

|-

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:: Row ''F'' remains and columns 2 and 7 remain:

:::{| class="wikitable"

:::{| border="1" cellpadding="5" cellspacing="0"

! !! 2 !! 7

|-

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:: Step 1—The matrix is not empty, so the algorithm proceeds.

:: Step 2—The lowest number of 1s in any column is one. Column 2 is the first column with one 1 and thus is selected (deterministically).:

:::{| class="wikitable"

! !! <span style="color:red">2</span> !! 7

|-

! ''F''

| <span style="color:red;font-weight:bold">1</span> || 1

|}

:: Row ''F'' has a 1 in column 2 and thus is selected (nondeterministically).

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::: Row ''F'' has a 1 in columns 2 and 7:

::::{| borderclass="1" cellpadding="5" cellspacing="0wikitable"

! !! <span style="color:blue">2</span> !! <span style="color:blue">7</span>

|-

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|}

::: Column 2 has a 1 in row ''F''; and column 7 has a 1 in row ''F''. Thus, row ''F'' is to be removed and columns 2 and 7 are to be removed:

::::{| borderclass="1" cellpadding="5" cellspacing="0wikitable"

! !! <span style="color:red">2</span> !! <span style="color:red">7</span>

|-

! <span style="color:blue">''F''</span>

| <span style="color:red;font-weight:bold">1</span> || <span style="color:red;font-weight:bold">1</span>

|}

::: No rows and no columns remain:

::::{| class="wikitable"

! &nbsp;

|}

::: Step 1—The matrix is empty, thus this branch of the algorithm terminates successfully.

::: As rows ''B'', ''D'', and ''F'' arehave been selected (step 4), the final solution in this branch is:

::::{| borderclass="1" cellpadding="5" cellspacing="0wikitable"

! !! 1 !! 2 !! 3 !! 4 !! 5 !! 6 !! 7

|-

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There are no branches at level 0, thus the algorithm terminates.

In summary, the algorithm determines there is only one exact cover: <math>\mathcal{{mathcal|S}^}{{sup|*</math>}} = {''B'', ''D'', ''F''}.

==Implementations==

[[Donald Knuth]]'s main purpose in describing Algorithm X was to demonstrate the utility of [[dancing links]]. Knuth showed that Algorithm X can be implemented efficiently on a computer using dancing links in a process Knuth calls ''"DLX"''. DLX uses the matrix representation of the [[exact cover]] problem, implemented as [[doubly linked list]]s of the 1s of the matrix: each 1 element has a link to the next 1 above, below, to the left, and to the right of itself. (Technically, because the lists are circular, this forms a [[torus]]). Because exact cover problems tend to be sparse, this representation is usually much more efficient in both size and processing time required. DLX then uses dancing links to quickly select permutations of rows as possible solutions and to efficiently backtrack (undo) mistaken guesses.<ref name="knuth" />

==See also==

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{{Reflist}}

*{{citation

| first = Donald E. | last = Knuth | authorlinkauthor-link = Donald Knuth

| contribution = Dancing links

| title = Millennial Perspectives in Computer Science: Proceedings of the 1999 Oxford-Microsoft Symposium in Honour of Sir Tony Hoare

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==External links==

*[https://www.ocf.berkeley.edu/~jchu/publicportal/sudoku/0011047.pdf Knuth's paper] - PDF file (also [https://arxiv.org/pdf/{{ArXiv|cs/0011047.pdf]}})

*[http://www-cs-faculty.stanford.edu/~uno/papers/dancing-color.ps.gz Knuth's Paper describing the Dancing Links optimization] - Gzip'd postscript file.