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'''[[Main Page|Home]] * [[People]] * Alen Shapiro'''
'''Alen David Shapiro''',<br/>
a British computer scientist, who as student of [[Donald Michie]] at Department of Machine Intelligence at [[University of Edinburgh]] researched on [https://en.wikipedia.org/wiki/Decision_tree decision tree] algorithms and [https://en.wikipedia.org/wiki/Decision_tree_learning decision tree learning] applied to chess. Alen Shapiro and [[Tim Niblett]], another of Michie's students, adopted [[Ross Quinlan|Ross Quinlan's]] [https://en.wikipedia.org/wiki/ID3_algorithm Iterative Dichotomiser 3] (ID3) algorithm for processing complex data <ref>[[Ross Quinlan]] ('''1986'''). ''Induction of Decision Trees''. Machine Learning, Vol. 1, No. 1</ref> for other employment at the chessboard, while they overcame <ref>[http://www.aiai.ed.ac.uk/~dm/dmcv.html D. Michie CV]</ref> its disadvantage that it yielded massively unwieldy and incomprehensible decision-rules with ''structured induction'', an interactive regime for generating machine-executable decision rules and configuring them into transparent concept-hierarchies. Niblett and Shapiro tested ID3 on the [[Endgame|endgame]] of [[KPK]], and found that decision trees generated by the algorithm 100% accurate.
<span id="CLESS"></span>
=CLESS=
In 1979/80, Alen Shapiro worked with [[Ivan Bratko]] and [[Zdenek Zdrahal]] on [[Pattern Recognition]] applied to Chess. In fact they used [[Bitboards]], called [https://en.wikipedia.org/wiki/Cellular_automaton cellular] 8x8 [[Array|arrays]], to implement their ''Cellular logic processing emulator for chess'' (CLESS) <ref>[[Zdenek Zdrahal|Zdenek Zdráhal]], [[Ivan Bratko]], [[Alen Shapiro]] ('''1981'''). ''[http://comjnl.oxfordjournals.org/content/24/3/263.abstract Recognition of Complex Patterns Using Cellular Arrays]''. [http://comjnl.oxfordjournals.org/content/24/3.toc The Computer Journal, Vol. 24, No. 3], pp. 263-270</ref> . CLESS used three kinds of instructions to recognize simple and more complex chess patterns:
# [[General Setwise Operations#Bitwisebooleanoperations|bitwise boolean operations]] without any interactions between squares
# [[General Setwise Operations#ShiftingBitboards|shifts]] as expand instructions
# [[Fill Algorithms|fill-like]] propagation instructions, internally using the first two kinds of instructions and conditions in loops
=Chess Endgames=
Quote by [[Maarten van Emden]] in ''I remember Donald Michie'' <ref>[http://vanemden.wordpress.com/2009/06/12/i-remember-donald-michie-1923-2007/ I remember Donald Michie (1923 – 2007) « A Programmers Place] by [[Maarten van Emden]], June 12, 2009</ref>:
In 1980 I spent another summer in Edinburgh as a guest of Donald Michie. Since the low point of 1975, thanks to assiduous and inventive joint pursuit of funding possibilities by Donald and [http://www.informatik.uni-trier.de/%7Eley/db/indices/a-tree/m/Michie:Jean_Hayes.html Jean], the Machine Intelligence Research Unit was alive with work focused on [[Endgame|chess endgames]]. There were students, including [[Tim Niblett]] and Alen Shapiro. [[Danny Kopec]] was there, perhaps formally as a student, but de facto as the resident chess consultant. [[Ivan Bratko]] visited frequently. Alen was the administrator of the dream computing environment of that time: a small [[PDP-11]] running [[Unix]].
=Structured Induction=
from [http://www.answers.com/topic/computer-chess-1 computer chess: Information from Answers.com] <ref>[http://www.sgi.com/tech/mlc/db/chess.names Title: Chess End-Game - King+Rook versus King+Pawn on a7]</ref><ref>[http://www2.ift.ulaval.ca/~mmarchand/ Mario Marchand] and [http://www.informatik.uni-trier.de/~ley/db/indices/a-tree/g/Golea:Mostefa.html Mostefa Golea] ('''1993'''). ''A Constructive Algorithm for Neural Decision Lists.'' [https://en.wikipedia.org/wiki/University_of_Ottawa University of Ottawa], from World Congress on Neural Networks: Proceedings of the 1993 Annual Meeting of the International Neural Network Society, vol. 3, pp. 560-563, Hillsdale, NJ: Erlbaum Associates. [http://www2.ift.ulaval.ca/~mmarchand/publications/wcnn93ndl.pdf pdf]</ref>:
In addition to purely factual discoveries, computer programs could help the chess expert fill the gaps of which codified chess knowledge is now seen mainly to consist. Knowledge-directed programs can support his endeavours to outline the missing framework and by semi-automatic generation of descriptions from expert-supplied examples to fill empty slots in the framework as it takes shape. Using a technique of Alen Shapiro and [[Tim Niblett|Timothy Niblett]] known as 'structured induction', Shapiro was able to generate a complete human-readable codification for adjudicating positions in the king-pawn–king-rook ending (pawn's side to move, pawn on a7) where none pre-existed. A side benefit subsequently extracted from this phenomenon was endowment of the program with the ability to document its own adjudications on demand with explanatory notes.
In the above-mentioned work the induction process was fuelled by hand-supplied examples. In some other cases success has been reported where the examples have been quarried by the program itself from large pre-computed databases. A recent de novo synthesis of knowledge in clinical cardiology by Ivan Bratko and colleagues employed just such an alternation between
(i) exhaustive derivation of brute facts from a logical model and
(ii) induction from these of an operational theory.
Sparked initially by the chess work, application is beginning to place emphasis on factual compilations as raw materials for automating the codification of new knowledge as a commercial product. The need to better understand the cognitive invariants with which the designer of codification languages must now come to terms is also leading to closer involvement of professional students of mind.
[[FILE:KRKPa7.JPG|none|border|text-bottom]]
Structured Induction Expert System <ref>Alen Shapiro ('''1987'''). ''Structured Induction in Expert Systems''. Turing Institute Press in association with Addison-Wesley Publishing Company, Workingham, UK. ISBN 0-201-178133</ref>
=AI as Sport=
Quote by [[John McCarthy]] from ''AI as Sport'' <ref>[[John McCarthy]] ('''1997'''). ''[http://science.sciencemag.org/content/276/5318/1518 AI as Sport]''. [[Science]], Vol. 276</ref><ref>[http://www-formal.stanford.edu/jmc/newborn/newborn.html AI as Sport] by [[John McCarthy]]</ref>:
Besides AI work aimed at tournament play, particular aspects of the game have illuminated the intellectual mechanisms involved. [[Barbara Liskov]] demonstrated that what chess books teach about how to win certain [[Endgame|endgames]] is not a program but more like a predicate comparing two positions to see if one is an improvement on the other. Such qualitative comparisons are an important feature of human intelligence and are needed for AI. [[Donald Michie]], [[Ivan Bratko]], [[Alen Shapiro]], [[David Wilkins]], and others have also used chess as a Drosophila to study intelligence. [[Monroe Newborn|Newborn]] ignores this work, because it is not oriented to tournament play.
=Selected Publications=
<ref>[http://ilk.uvt.nl/icga/journal/docs/References.pdf ICGA Reference Database] (pdf)</ref> <ref>[http://www.informatik.uni-trier.de/~ley/db/indices/a-tree/s/Shapiro:Alen.html dblp: Alen Shapiro]</ref>
* [[Zdenek Zdrahal|Zdenek Zdráhal]], [[Ivan Bratko]], [[Alen Shapiro]] ('''1981'''). ''[http://comjnl.oxfordjournals.org/content/24/3/263.abstract Recognition of Complex Patterns Using Cellular Arrays]''. [http://comjnl.oxfordjournals.org/content/24/3.toc The Computer Journal, Vol. 24, No. 3]
* [[Alen Shapiro]], [[Tim Niblett]] ('''1982'''). ''Automatic Induction of Classification Rules for Chess End game.'' [[Advances in Computer Chess 3]]
* [[Alen Shapiro]] ('''1983'''). ''The Role of Structured Induction in Expert Systems''. [[University of Edinburgh]], Machine Intelligence Research Unit (Ph.D. thesis) <ref>[http://archive.ics.uci.edu/ml/datasets/Chess+%28King-Rook+vs.+King-Pawn%29 UCI Machine Learning Repository: Chess (King-Rook vs. King-Pawn) Data Set]</ref>
* [[Alen Shapiro]], [[Donald Michie]] ('''1986'''). ''A Self-commenting Facility for Inductively Synthesised Endgame Expertise''. [[Advances in Computer Chess 4]]
* [[Alen Shapiro]] ('''1987'''). ''Structured Induction in Expert Systems''. Turing Institute Press in association with Addison-Wesley Publishing Company, Workingham, UK. ISBN 0-201-178133. [http://www.amazon.com/exec/obidos/ASIN/0201178133/acmorg-20 amazon]<ref>[[Dap Hartmann]] ('''1988'''). Alen D. Shapiro: ''Structured Induction in Expert Systems''. [[ICGA Journal#11_4|ICCA Journal, Vol. 11, No. 4]]</ref>.
=External Links=
* [http://archive.ics.uci.edu/ml/datasets/Chess+%28King-Rook+vs.+King-Pawn%29 UCI Machine Learning Repository: Chess (King-Rook vs. King-Pawn) Data Set] by [[Alen Shapiro]] <ref>[https://scholar.google.com/citations?user=RDky42sAAAAJ&hl=en Dheeru Dua], [https://scholar.google.com/citations?user=i3GbatoAAAAJ&hl=en Efi Karra Taniskidou] ('''2017'''). ''[http://archive.ics.uci.edu/ml UCI Machine Learning Repository]''. [https://en.wikipedia.org/wiki/University_of_California,_Irvine University of California, Irvine], School of Information and Computer Science</ref>
=References=
<references />
'''[[Engines|Up one level]]'''
'''Alen David Shapiro''',<br/>
a British computer scientist, who as student of [[Donald Michie]] at Department of Machine Intelligence at [[University of Edinburgh]] researched on [https://en.wikipedia.org/wiki/Decision_tree decision tree] algorithms and [https://en.wikipedia.org/wiki/Decision_tree_learning decision tree learning] applied to chess. Alen Shapiro and [[Tim Niblett]], another of Michie's students, adopted [[Ross Quinlan|Ross Quinlan's]] [https://en.wikipedia.org/wiki/ID3_algorithm Iterative Dichotomiser 3] (ID3) algorithm for processing complex data <ref>[[Ross Quinlan]] ('''1986'''). ''Induction of Decision Trees''. Machine Learning, Vol. 1, No. 1</ref> for other employment at the chessboard, while they overcame <ref>[http://www.aiai.ed.ac.uk/~dm/dmcv.html D. Michie CV]</ref> its disadvantage that it yielded massively unwieldy and incomprehensible decision-rules with ''structured induction'', an interactive regime for generating machine-executable decision rules and configuring them into transparent concept-hierarchies. Niblett and Shapiro tested ID3 on the [[Endgame|endgame]] of [[KPK]], and found that decision trees generated by the algorithm 100% accurate.
<span id="CLESS"></span>
=CLESS=
In 1979/80, Alen Shapiro worked with [[Ivan Bratko]] and [[Zdenek Zdrahal]] on [[Pattern Recognition]] applied to Chess. In fact they used [[Bitboards]], called [https://en.wikipedia.org/wiki/Cellular_automaton cellular] 8x8 [[Array|arrays]], to implement their ''Cellular logic processing emulator for chess'' (CLESS) <ref>[[Zdenek Zdrahal|Zdenek Zdráhal]], [[Ivan Bratko]], [[Alen Shapiro]] ('''1981'''). ''[http://comjnl.oxfordjournals.org/content/24/3/263.abstract Recognition of Complex Patterns Using Cellular Arrays]''. [http://comjnl.oxfordjournals.org/content/24/3.toc The Computer Journal, Vol. 24, No. 3], pp. 263-270</ref> . CLESS used three kinds of instructions to recognize simple and more complex chess patterns:
# [[General Setwise Operations#Bitwisebooleanoperations|bitwise boolean operations]] without any interactions between squares
# [[General Setwise Operations#ShiftingBitboards|shifts]] as expand instructions
# [[Fill Algorithms|fill-like]] propagation instructions, internally using the first two kinds of instructions and conditions in loops
=Chess Endgames=
Quote by [[Maarten van Emden]] in ''I remember Donald Michie'' <ref>[http://vanemden.wordpress.com/2009/06/12/i-remember-donald-michie-1923-2007/ I remember Donald Michie (1923 – 2007) « A Programmers Place] by [[Maarten van Emden]], June 12, 2009</ref>:
In 1980 I spent another summer in Edinburgh as a guest of Donald Michie. Since the low point of 1975, thanks to assiduous and inventive joint pursuit of funding possibilities by Donald and [http://www.informatik.uni-trier.de/%7Eley/db/indices/a-tree/m/Michie:Jean_Hayes.html Jean], the Machine Intelligence Research Unit was alive with work focused on [[Endgame|chess endgames]]. There were students, including [[Tim Niblett]] and Alen Shapiro. [[Danny Kopec]] was there, perhaps formally as a student, but de facto as the resident chess consultant. [[Ivan Bratko]] visited frequently. Alen was the administrator of the dream computing environment of that time: a small [[PDP-11]] running [[Unix]].
=Structured Induction=
from [http://www.answers.com/topic/computer-chess-1 computer chess: Information from Answers.com] <ref>[http://www.sgi.com/tech/mlc/db/chess.names Title: Chess End-Game - King+Rook versus King+Pawn on a7]</ref><ref>[http://www2.ift.ulaval.ca/~mmarchand/ Mario Marchand] and [http://www.informatik.uni-trier.de/~ley/db/indices/a-tree/g/Golea:Mostefa.html Mostefa Golea] ('''1993'''). ''A Constructive Algorithm for Neural Decision Lists.'' [https://en.wikipedia.org/wiki/University_of_Ottawa University of Ottawa], from World Congress on Neural Networks: Proceedings of the 1993 Annual Meeting of the International Neural Network Society, vol. 3, pp. 560-563, Hillsdale, NJ: Erlbaum Associates. [http://www2.ift.ulaval.ca/~mmarchand/publications/wcnn93ndl.pdf pdf]</ref>:
In addition to purely factual discoveries, computer programs could help the chess expert fill the gaps of which codified chess knowledge is now seen mainly to consist. Knowledge-directed programs can support his endeavours to outline the missing framework and by semi-automatic generation of descriptions from expert-supplied examples to fill empty slots in the framework as it takes shape. Using a technique of Alen Shapiro and [[Tim Niblett|Timothy Niblett]] known as 'structured induction', Shapiro was able to generate a complete human-readable codification for adjudicating positions in the king-pawn–king-rook ending (pawn's side to move, pawn on a7) where none pre-existed. A side benefit subsequently extracted from this phenomenon was endowment of the program with the ability to document its own adjudications on demand with explanatory notes.
In the above-mentioned work the induction process was fuelled by hand-supplied examples. In some other cases success has been reported where the examples have been quarried by the program itself from large pre-computed databases. A recent de novo synthesis of knowledge in clinical cardiology by Ivan Bratko and colleagues employed just such an alternation between
(i) exhaustive derivation of brute facts from a logical model and
(ii) induction from these of an operational theory.
Sparked initially by the chess work, application is beginning to place emphasis on factual compilations as raw materials for automating the codification of new knowledge as a commercial product. The need to better understand the cognitive invariants with which the designer of codification languages must now come to terms is also leading to closer involvement of professional students of mind.
[[FILE:KRKPa7.JPG|none|border|text-bottom]]
Structured Induction Expert System <ref>Alen Shapiro ('''1987'''). ''Structured Induction in Expert Systems''. Turing Institute Press in association with Addison-Wesley Publishing Company, Workingham, UK. ISBN 0-201-178133</ref>
=AI as Sport=
Quote by [[John McCarthy]] from ''AI as Sport'' <ref>[[John McCarthy]] ('''1997'''). ''[http://science.sciencemag.org/content/276/5318/1518 AI as Sport]''. [[Science]], Vol. 276</ref><ref>[http://www-formal.stanford.edu/jmc/newborn/newborn.html AI as Sport] by [[John McCarthy]]</ref>:
Besides AI work aimed at tournament play, particular aspects of the game have illuminated the intellectual mechanisms involved. [[Barbara Liskov]] demonstrated that what chess books teach about how to win certain [[Endgame|endgames]] is not a program but more like a predicate comparing two positions to see if one is an improvement on the other. Such qualitative comparisons are an important feature of human intelligence and are needed for AI. [[Donald Michie]], [[Ivan Bratko]], [[Alen Shapiro]], [[David Wilkins]], and others have also used chess as a Drosophila to study intelligence. [[Monroe Newborn|Newborn]] ignores this work, because it is not oriented to tournament play.
=Selected Publications=
<ref>[http://ilk.uvt.nl/icga/journal/docs/References.pdf ICGA Reference Database] (pdf)</ref> <ref>[http://www.informatik.uni-trier.de/~ley/db/indices/a-tree/s/Shapiro:Alen.html dblp: Alen Shapiro]</ref>
* [[Zdenek Zdrahal|Zdenek Zdráhal]], [[Ivan Bratko]], [[Alen Shapiro]] ('''1981'''). ''[http://comjnl.oxfordjournals.org/content/24/3/263.abstract Recognition of Complex Patterns Using Cellular Arrays]''. [http://comjnl.oxfordjournals.org/content/24/3.toc The Computer Journal, Vol. 24, No. 3]
* [[Alen Shapiro]], [[Tim Niblett]] ('''1982'''). ''Automatic Induction of Classification Rules for Chess End game.'' [[Advances in Computer Chess 3]]
* [[Alen Shapiro]] ('''1983'''). ''The Role of Structured Induction in Expert Systems''. [[University of Edinburgh]], Machine Intelligence Research Unit (Ph.D. thesis) <ref>[http://archive.ics.uci.edu/ml/datasets/Chess+%28King-Rook+vs.+King-Pawn%29 UCI Machine Learning Repository: Chess (King-Rook vs. King-Pawn) Data Set]</ref>
* [[Alen Shapiro]], [[Donald Michie]] ('''1986'''). ''A Self-commenting Facility for Inductively Synthesised Endgame Expertise''. [[Advances in Computer Chess 4]]
* [[Alen Shapiro]] ('''1987'''). ''Structured Induction in Expert Systems''. Turing Institute Press in association with Addison-Wesley Publishing Company, Workingham, UK. ISBN 0-201-178133. [http://www.amazon.com/exec/obidos/ASIN/0201178133/acmorg-20 amazon]<ref>[[Dap Hartmann]] ('''1988'''). Alen D. Shapiro: ''Structured Induction in Expert Systems''. [[ICGA Journal#11_4|ICCA Journal, Vol. 11, No. 4]]</ref>.
=External Links=
* [http://archive.ics.uci.edu/ml/datasets/Chess+%28King-Rook+vs.+King-Pawn%29 UCI Machine Learning Repository: Chess (King-Rook vs. King-Pawn) Data Set] by [[Alen Shapiro]] <ref>[https://scholar.google.com/citations?user=RDky42sAAAAJ&hl=en Dheeru Dua], [https://scholar.google.com/citations?user=i3GbatoAAAAJ&hl=en Efi Karra Taniskidou] ('''2017'''). ''[http://archive.ics.uci.edu/ml UCI Machine Learning Repository]''. [https://en.wikipedia.org/wiki/University_of_California,_Irvine University of California, Irvine], School of Information and Computer Science</ref>
=References=
<references />
'''[[Engines|Up one level]]'''
