J. J. Merelo-Guervós >
Algorithm-MasterMind-v0.4.5 >
Algorithm::MasterMind

Module Version: 0.4.5
- NAME
- VERSION
- SYNOPSIS
- DESCRIPTION
- INTERFACE
- new ( $options )
- add_rule( $combination, $result)
- check_combination( $secret_code, $combination )
- distance( $object )
- check_combination_old ( $secret_code, $combination )
- check_rule ($rule, $combination)
- issue_first ()
- start_from ()
- issue_first_Knuth
- issue_next()
- feedback()
- guesses()
- evaluated()
- number_of_rules ()
- rules()
- matches( $string )
- hashify ( $string )
- not_in_combination( $string)
- random_combination
- partitions
- all_combinations
- entropy( $string )
- distance_taxicab( $string )
- distance_chebyshev( $string )
- all_responses()
- random_string
- response_as_string ( $response )

- CONFIGURATION AND ENVIRONMENT
- DEPENDENCIES
- INCOMPATIBILITIES
- BUGS AND LIMITATIONS
- SEE ALSO
- AUTHOR
- LICENCE AND COPYRIGHT
- DISCLAIMER OF WARRANTY

Algorithm::MasterMind - Framework for algorithms that solve the MasterMind game

This document describes Algorithm::MasterMind version 0.4.1

use Algorithm::MasterMind; use Algorithm::MasterMind::Solver; # Change "solver" to your own. my $solver = new Algorithm::MasterMind::Solver $options; my $first_string = $solver->issue_first(); $solver->feedback( check_combination( $secret_code, $first_string) ); my $played_string = $solver->issue_next; $solver->feedback( check_combination( $secret_code, $played_string) ); #And so on until solution is found

Includes common functions used in Mastermind solvers; it should not be used directly, but from derived classes. See examples in Algorithm::MasterMind::Random, for instance.

Normally to be called from derived classes

Adds a rule (set of combination and its result as a hash) to the set of rules. These rules represent the information we've got on the secret code.

Checks a combination against the secret code, returning a hashref with the number of blacks (correct in position) and whites (correct in color, not position)

Computes distance to a consistent combination, computed as the number of blacks and whites that need change to become a consistent combination.

Old way of checking combinations, eliminated after profiling

Same as `check_combination`

, except that a rule contains a combination and how it scored against the secret code

Issues the first combination, which might be generated in a particular way

Used when you want to create an solver once it's been partially solved; it contains partial solutions.

First combination looking like AABC for the normal mastermind. Proposed by Knuth in one of his original papers.

Issues the next combination

Obtain the result to the last combination played

Total number of guesses

Total number of combinations checked to issue result

Returns the number of rules in the algorithm

Returns the rules (combinations, blacks, whites played so far) as a reference to array

Returns a hash with the number of matches, and whether it matches every rule with the number of blacks and whites it obtains with each of them

Turns a string into a hash, to help with comparisons. Used internally, mainly.

Returns the letters from the alphabet that are _not_ in this combination. Might be useful for certain strategies.

Combines randomly the alphabet, issuing, you guessed it, a random combination.

From a set of combinations, returns the "partitions", that is, the number of combinations that would return every set of black and white response. Inputs an array, returns a hash keyed to the combination, each key containing a value corresponding to the number of elements in each partition.

Returns all possible combinations of the current alphabet and length in an array. Be careful with that, it could very easily fill up your memory, depending on length and alphabet size.

Computes the string entropy

Computes the sums of taxicab distances to all combinations in the game, and returns it as [$distance, $matches]

Computes the Chebyshev distance, that is, the max of distances in all dimensions. Returns as a arrayref with [$distance, matches]

Returns all possible responses (combination of black and white pegs) for the combination length

Returns a random string in with the length and alphabet defined

From a hash that uses keys `blacks`

and `whites`

, returns a string "xb-yw" in a standard format that can be used for comparing.

Algorithm::MasterMind requires no configuration files or environment variables.

Algorithm::Evolutionary, but only for one of the strategies. Algorithm::Combinatorics, used to generate combinations and for exhaustive search strategies.

None reported.

No bugs have been reported.

Please report any bugs or feature requests to `bug-algorithm-mastermind@rt.cpan.org`

, or through the web interface at http://rt.cpan.org.

Other modules in CPAN which you might find more useful than this one are at Games::Mastermind::Solver, which I didn't use and extend for no reason, although I should have. Also Games::Mastermind::Cracker.

Formerly, you could try and play this game at http://geneura.ugr.es/~jmerelo/GenMM/mm-eda.cgi, restricted to 4 pegs and 6 colors. It's, for the time being, under reparations. The program `mm-eda.cgi`

should also be available in the `apps`

directory of this distribution.

The development of this projects is hosted at sourceforge, https://sourceforge.net/projects/opeal/develop, check it out for the latest bleeding edge release. In fact, right now this module is at least a year away from the latest development.

If you use any of these modules for your own research, we would very grateful if you would reference the papers that describe this, such as this one:

@article{merelo2010finding, title={{Finding Better Solutions to the Mastermind Puzzle Using Evolutionary Algorithms}}, author={Merelo-Guerv{\'o}s, J. and Runarsson, T.}, journal={Applications of Evolutionary Computation}, pages={121--130}, year={2010}, publisher={Springer} }

or

@inproceedings{DBLP:conf/cec/GuervosMC11, author = {Juan-J. Merelo-Guerv{\'o}s and Antonio-Miguel Mora and Carlos Cotta}, title = {Optimizing worst-case scenario in evolutionary solutions to the {MasterMind} puzzle}, booktitle = {IEEE Congress on Evolutionary Computation}, year = {2011}, pages = {2669-2676}, ee = {http://dx.doi.org/10.1109/CEC.2011.5949952}, crossref = {DBLP:conf/cec/2011}, bibsource = {DBLP, http://dblp.uni-trier.de} } @proceedings{DBLP:conf/cec/2011, title = {Proceedings of the IEEE Congress on Evolutionary Computation, CEC 2011, New Orleans, LA, USA, 5-8 June, 2011}, booktitle = {IEEE Congress on Evolutionary Computation}, publisher = {IEEE}, year = {2011}, isbn = {978-1-4244-7834-7}, ee = {http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=5936494}, bibsource = {DBLP, http://dblp.uni-trier.de} }

JJ Merelo `<jj@merelo.net>`

Copyright (c) 2009, JJ Merelo `<jj@merelo.net>`

. All rights reserved.

This module is free software; you can redistribute it and/or modify it under the same terms as Perl itself. See perlartistic.

BECAUSE THIS SOFTWARE IS LICENSED FREE OF CHARGE, THERE IS NO WARRANTY FOR THE SOFTWARE, TO THE EXTENT PERMITTED BY APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT HOLDERS AND/OR OTHER PARTIES PROVIDE THE SOFTWARE "AS IS" WITHOUT WARRANTY OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE SOFTWARE IS WITH YOU. SHOULD THE SOFTWARE PROVE DEFECTIVE, YOU ASSUME THE COST OF ALL NECESSARY SERVICING, REPAIR, OR CORRECTION.

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