Difference between revisions of "Jay Scott"

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(Created page with "'''Home * People * Jay Scott''' FILE:jayscott.jpg|border|right|thumb|link=http://satirist.org/|Jay Scott <ref>[http://satirist.org/ Jay Scott at satirist....")
 
 
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[[FILE:jayscott.jpg|border|right|thumb|link=http://satirist.org/|Jay Scott <ref>[http://satirist.org/ Jay Scott at satirist.org], self portrait, January 2000</ref> ]]  
 
[[FILE:jayscott.jpg|border|right|thumb|link=http://satirist.org/|Jay Scott <ref>[http://satirist.org/ Jay Scott at satirist.org], self portrait, January 2000</ref> ]]  
  
'''Jay J.P. Scott''',
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'''Jay J.P. Scott''',<br/>
 
an American mathematician with expertise in [[Learning|machine learning]] who works for ''The Math Forum'' at [https://en.wikipedia.org/wiki/Drexel_University Drexel University] in [https://en.wikipedia.org/wiki/Philadelphia Philadelphia] <ref>[http://mathforum.org/ The Math Forum @ Drexel University]</ref>. He maintains the ''satirist.org'' websites <ref>[http://satirist.org/ Jay Scott at satirist.org]</ref>, including ''Machine Learning in Games'', where he describes programs relying on heuristic [[Search|search]] [[Algorithms|algorithms]], [[Genetic Programming#GeneticAlgorithm|genetic algorithms]], [[Neural Networks|neural networks]], and  [[Temporal Difference Learning|temporal differences]]. Jay Scott was an early [[GNU Chess]] contributor, mentioned as co-author in the [[ACM 1987]] booklet <ref>[http://www.computerhistory.org/chess/full_record.php?iid=doc-431614f6cabbd The ACM's Eighteenth North American Computer Chess Championship] from [[The Computer History Museum]], as [http://archive.computerhistory.org/projects/chess/related_materials/text/3-1%20and%203-2%20and%203-3%20and%204-3.1987_18th_NACCC/1987%20NACCC.062303063.sm.pdf pdf]</ref>. He is further author of the experimental chess program [[Kon]] to study automated learning of [[Search|search]] control, which used a [[Best-First|breadth-first]] search and kept the entire [[Search Tree|tree]] in [[Memory|memory]] <ref>[https://www.stmintz.com/ccc/index.php?id=13454 playing style from search (was Re: Junior's long lines)] by [[Jay Scott]], [[CCC]], December 29, 1997</ref>.  
 
an American mathematician with expertise in [[Learning|machine learning]] who works for ''The Math Forum'' at [https://en.wikipedia.org/wiki/Drexel_University Drexel University] in [https://en.wikipedia.org/wiki/Philadelphia Philadelphia] <ref>[http://mathforum.org/ The Math Forum @ Drexel University]</ref>. He maintains the ''satirist.org'' websites <ref>[http://satirist.org/ Jay Scott at satirist.org]</ref>, including ''Machine Learning in Games'', where he describes programs relying on heuristic [[Search|search]] [[Algorithms|algorithms]], [[Genetic Programming#GeneticAlgorithm|genetic algorithms]], [[Neural Networks|neural networks]], and  [[Temporal Difference Learning|temporal differences]]. Jay Scott was an early [[GNU Chess]] contributor, mentioned as co-author in the [[ACM 1987]] booklet <ref>[http://www.computerhistory.org/chess/full_record.php?iid=doc-431614f6cabbd The ACM's Eighteenth North American Computer Chess Championship] from [[The Computer History Museum]], as [http://archive.computerhistory.org/projects/chess/related_materials/text/3-1%20and%203-2%20and%203-3%20and%204-3.1987_18th_NACCC/1987%20NACCC.062303063.sm.pdf pdf]</ref>. He is further author of the experimental chess program [[Kon]] to study automated learning of [[Search|search]] control, which used a [[Best-First|breadth-first]] search and kept the entire [[Search Tree|tree]] in [[Memory|memory]] <ref>[https://www.stmintz.com/ccc/index.php?id=13454 playing style from search (was Re: Junior's long lines)] by [[Jay Scott]], [[CCC]], December 29, 1997</ref>.  
  

Latest revision as of 11:37, 21 June 2018

Home * People * Jay Scott

Jay Scott [1]

Jay J.P. Scott,
an American mathematician with expertise in machine learning who works for The Math Forum at Drexel University in Philadelphia [2]. He maintains the satirist.org websites [3], including Machine Learning in Games, where he describes programs relying on heuristic search algorithms, genetic algorithms, neural networks, and temporal differences. Jay Scott was an early GNU Chess contributor, mentioned as co-author in the ACM 1987 booklet [4]. He is further author of the experimental chess program Kon to study automated learning of search control, which used a breadth-first search and kept the entire tree in memory [5].

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Machine Learning in Games

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