https://www.chessprogramming.org/index.php?title=Meep&feed=atom&action=history
Meep - Revision history
2024-03-29T14:41:46Z
Revision history for this page on the wiki
MediaWiki 1.30.1
https://www.chessprogramming.org/index.php?title=Meep&diff=19541&oldid=prev
GerdIsenberg at 09:13, 20 June 2020
2020-06-20T09:13:54Z
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<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>* [[:Category:Volker Kriegel|Volker Kriegel]] - Three Or Two In One, [http://www.discogs.com/Volker-Kriegel-Lift/release/726875 Lift!], 1973, [https://en.wikipedia.org/wiki/YouTube YouTube] Video</div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>* [[:Category:Volker Kriegel|Volker Kriegel]] - Three Or Two In One, [http://www.discogs.com/Volker-Kriegel-Lift/release/726875 Lift!], 1973, [https://en.wikipedia.org/wiki/YouTube YouTube] Video</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>: feat: [[:Category:Eberhard Weber|Eberhard Weber]], [[:Category:John Marshall|John Marshall]], [https://en.wikipedia.org/wiki/Stan_Sulzmann Stan Sulzmann], [https://en.wikipedia.org/wiki/John_Taylor_%28jazz%29 John Taylor], [https://de.wikipedia.org/wiki/Cees_See Cees See], [[:Category:Zbigniew Seifert|Zbigniew Seifert]]</div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>: feat: [[:Category:Eberhard Weber|Eberhard Weber]], [[:Category:John Marshall|John Marshall]], [https://en.wikipedia.org/wiki/Stan_Sulzmann Stan Sulzmann], [https://en.wikipedia.org/wiki/John_Taylor_%28jazz%29 John Taylor], [https://de.wikipedia.org/wiki/Cees_See Cees See], [[:Category:Zbigniew Seifert|Zbigniew Seifert]]</div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>: {{#evu:https://www.youtube.com/watch?v=<del class="diffchange diffchange-inline">neBBmEAHQoQ</del>|alignment=left|valignment=top}}</div></td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>: {{#evu:https://www.youtube.com/watch?v=<ins class="diffchange diffchange-inline">NmiEyjWgkRc</ins>|alignment=left|valignment=top}}</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>=References=  </div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>=References=  </div></td></tr>
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GerdIsenberg
https://www.chessprogramming.org/index.php?title=Meep&diff=11795&oldid=prev
GerdIsenberg at 11:03, 25 April 2019
2019-04-25T11:03:36Z
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<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div><references /></div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div><references /></div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;"></del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>'''[[Engines|Up one level]]'''</div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>'''[[Engines|Up one level]]'''</div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">[[Category:Thesis]]</ins></div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>[[Category:Volker Kriegel]]</div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>[[Category:Volker Kriegel]]</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>[[Category:John Marshall]]</div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>[[Category:John Marshall]]</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>[[Category:Zbigniew Seifert]]</div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>[[Category:Zbigniew Seifert]]</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>[[Category:Eberhard Weber]]</div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>[[Category:Eberhard Weber]]</div></td></tr>
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GerdIsenberg
https://www.chessprogramming.org/index.php?title=Meep&diff=6294&oldid=prev
GerdIsenberg at 13:36, 25 August 2018
2018-08-25T13:36:09Z
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<td colspan="2" style="background-color: white; color:black; text-align: center;">Revision as of 13:36, 25 August 2018</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l91" >Line 91:</td>
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<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>* [[Joel Veness]], [[David Silver]], [[William Uther]], [[Alan Blair]] ('''2009'''). ''[http://papers.nips.cc/paper/3722-bootstrapping-from-game-tree-search Bootstrapping from Game Tree Search]''. [http://jveness.info/publications/nips2009%20-%20bootstrapping%20from%20game%20tree%20search.pdf pdf] <ref>[http://www.talkchess.com/forum/viewtopic.php?start=0&t=31667 A paper about parameter tuning] by [[Rémi Coulom]], [[CCC]], January 12, 2010</ref></div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>* [[Joel Veness]], [[David Silver]], [[William Uther]], [[Alan Blair]] ('''2009'''). ''[http://papers.nips.cc/paper/3722-bootstrapping-from-game-tree-search Bootstrapping from Game Tree Search]''. [http://jveness.info/publications/nips2009%20-%20bootstrapping%20from%20game%20tree%20search.pdf pdf] <ref>[http://www.talkchess.com/forum/viewtopic.php?start=0&t=31667 A paper about parameter tuning] by [[Rémi Coulom]], [[CCC]], January 12, 2010</ref></div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>* [[Joel Veness]] ('''2011'''). ''Approximate Universal Artificial Intelligence and Self-Play Learning for Games''. Ph.D. thesis, [https://en.wikipedia.org/wiki/University_of_New_South_Wales University of New South Wales], supervisors: [[Kee Siong Ng]], [[Marcus Hutter]], [[Alan Blair]], [[William Uther]], [[John Lloyd]]; [http://jveness.info/publications/veness_phd_thesis_final.pdf pdf]</div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>* [[Joel Veness]] ('''2011'''). ''Approximate Universal Artificial Intelligence and Self-Play Learning for Games''. Ph.D. thesis, [https://en.wikipedia.org/wiki/University_of_New_South_Wales University of New South Wales], supervisors: [[Kee Siong Ng]], [[Marcus Hutter]], [[Alan Blair]], [[William Uther]], [[John Lloyd]]; [http://jveness.info/publications/veness_phd_thesis_final.pdf pdf]</div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>* [[István Szita]] ('''2012'''). ''[http://link.springer.com/chapter/10.1007%2F978-3-642-27645-3_17 Reinforcement Learning in Games]''. in [[Marco Wiering]], [http://martijnvanotterlo.nl/ Martijn Van Otterlo] (eds.). ''<del class="diffchange diffchange-inline">[https://scholar.google.com/citations?view_op=view_citation&hl=en&user=xVas0I8AAAAJ&citation_for_view=xVas0I8AAAAJ:abG-DnoFyZgC </del>Reinforcement learning: State-of-the-art<del class="diffchange diffchange-inline">]</del>''. [http://link.springer.com/book/10.1007/978-3-642-27645-3 Adaptation, Learning, and Optimization, Vol. 12], [https://en.wikipedia.org/wiki/Springer_Science%2BBusiness_Media Springer]</div></td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>* [[István Szita]] ('''2012'''). ''[http://link.springer.com/chapter/10.1007%2F978-3-642-27645-3_17 Reinforcement Learning in Games]''. in [[Marco Wiering]], [http://martijnvanotterlo.nl/ Martijn Van Otterlo] (eds.). ''Reinforcement learning: State-of-the-art''. [http://link.springer.com/book/10.1007/978-3-642-27645-3 Adaptation, Learning, and Optimization, Vol. 12], [https://en.wikipedia.org/wiki/Springer_Science%2BBusiness_Media Springer]</div></td></tr>
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<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>=Forum Posts=  </div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>=Forum Posts=  </div></td></tr>
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GerdIsenberg
https://www.chessprogramming.org/index.php?title=Meep&diff=5411&oldid=prev
GerdIsenberg at 14:20, 3 July 2018
2018-07-03T14:20:45Z
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<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>: [https://en.wikipedia.org/wiki/Garter_%28stockings%29#Garter_belts Wearing suspenders or garter belts from Wikipedia]</div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>: [https://en.wikipedia.org/wiki/Garter_%28stockings%29#Garter_belts Wearing suspenders or garter belts from Wikipedia]</div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>* [[<del class="diffchange diffchange-inline">Videos#VolkerKriegel</del>|Volker Kriegel]] - Three Or Two In One, [http://www.discogs.com/Volker-Kriegel-Lift/release/726875 Lift!], 1973, [https://en.wikipedia.org/wiki/YouTube YouTube] Video</div></td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>* [[<ins class="diffchange diffchange-inline">:Category:Volker Kriegel</ins>|Volker Kriegel]] - Three Or Two In One, [http://www.discogs.com/Volker-Kriegel-Lift/release/726875 Lift!], 1973, [https://en.wikipedia.org/wiki/YouTube YouTube] Video</div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>: feat: [[<del class="diffchange diffchange-inline">Videos#EberhardWeber</del>|Eberhard Weber]], [[<del class="diffchange diffchange-inline">Videos#JohnMarshall</del>|John Marshall]], [https://en.wikipedia.org/wiki/Stan_Sulzmann Stan Sulzmann], [https://en.wikipedia.org/wiki/John_Taylor_%28jazz%29 John Taylor], [https://de.wikipedia.org/wiki/Cees_See Cees See], [[<del class="diffchange diffchange-inline">Videos#ZbigniewSeifert</del>|Zbigniew Seifert]]</div></td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>: feat: [[<ins class="diffchange diffchange-inline">:Category:Eberhard Weber</ins>|Eberhard Weber]], [[<ins class="diffchange diffchange-inline">:Category:John Marshall</ins>|John Marshall]], [https://en.wikipedia.org/wiki/Stan_Sulzmann Stan Sulzmann], [https://en.wikipedia.org/wiki/John_Taylor_%28jazz%29 John Taylor], [https://de.wikipedia.org/wiki/Cees_See Cees See], [[<ins class="diffchange diffchange-inline">:Category:Zbigniew Seifert</ins>|Zbigniew Seifert]]</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>: {{#evu:https://www.youtube.com/watch?v=neBBmEAHQoQ|alignment=left|valignment=top}}</div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>: {{#evu:https://www.youtube.com/watch?v=neBBmEAHQoQ|alignment=left|valignment=top}}</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td></tr>
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<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>'''[[Engines|Up one level]]'''</div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>'''[[Engines|Up one level]]'''</div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">[[Category:Volker Kriegel]]</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">[[Category:John Marshall]]</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">[[Category:Zbigniew Seifert]]</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">[[Category:Eberhard Weber]]</ins></div></td></tr>
</table>
GerdIsenberg
https://www.chessprogramming.org/index.php?title=Meep&diff=4648&oldid=prev
GerdIsenberg at 21:59, 23 June 2018
2018-06-23T21:59:02Z
<p></p>
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<td colspan="2" style="background-color: white; color:black; text-align: center;">Revision as of 21:59, 23 June 2018</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l4" >Line 4:</td>
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<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>'''Meep''',<br/></div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>'''Meep''',<br/></div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>an experimental chess engine as subject of research on [[Learning|machine learning]] techniques and [[Automated Tuning|automated tuning]], written by [[Joel Veness]], supported by [[David Silver]], [[William Uther]], and [[Alan Blair]], as elaborated in their 2009 research paper this page is based on <ref>[[Joel Veness]], [[David Silver]], [[William Uther]], [[Alan Blair]] ('''2009'''). ''[http://papers.nips.cc/paper/3722-bootstrapping-from-game-tree-search Bootstrapping from Game Tree Search]''. [http://jveness.info/publications/nips2009%20-%20bootstrapping%20from%20game%20tree%20search.pdf pdf]</ref> , and in Joel Veness' Ph.D. thesis <ref>[[Joel Veness]] ('''2011'''). ''Approximate Universal Artificial Intelligence and Self-Play Learning for Games''. Ph.D. thesis, [https://en.wikipedia.org/wiki/University_of_New_South_Wales University of New South Wales], supervisors: [[Kee Siong Ng]], [[Marcus Hutter]], [[Alan Blair]], [[William Uther]], [[John Lloyd]]; [http://jveness.info/publications/veness_phd_thesis_final.pdf pdf]</ref> . Meep is based on the <del class="diffchange diffchange-inline">[[UCI]] compliant </del>tournament chess engine [[Bodo]], where the hand-crafted [[Evaluation Function|evaluation function]] is replaced by a weighted [https://en.wikipedia.org/wiki/Linear_combination linear combination] of 1812 features. Given a position s, a [https://en.wikipedia.org/wiki/Feature_vector feature vector] Φ(s) can be constructed from the 1812 numeric values of each feature. The majority of these features are binary. Φ(s) is typically sparse, with approximately 100 features active in any given position. Five wellknown, chess specific feature construction concepts, [[Material|material]], [[Piece-Square Tables|piece square tables]], [[Pawn Structure|pawn structure]], [[Mobility|mobility]] and [[King Safety|king safety]] were used to generate the 1812 distinct features. In a training mode with various search frameworks, Meep learns from self-play to adjust the weights of its evaluation function towards the value of the deep search. A tournament mode is later used to verify the [[Playing Strength|strength]] of a trained weight configuration.  </div></td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>an experimental chess engine as subject of research on [[Learning|machine learning]] techniques and [[Automated Tuning|automated tuning]], written by [[Joel Veness]], supported by [[David Silver]], [[William Uther]], and [[Alan Blair]], as elaborated in their 2009 research paper this page is based on <ref>[[Joel Veness]], [[David Silver]], [[William Uther]], [[Alan Blair]] ('''2009'''). ''[http://papers.nips.cc/paper/3722-bootstrapping-from-game-tree-search Bootstrapping from Game Tree Search]''. [http://jveness.info/publications/nips2009%20-%20bootstrapping%20from%20game%20tree%20search.pdf pdf]</ref> , and in Joel Veness' Ph.D. thesis <ref>[[Joel Veness]] ('''2011'''). ''Approximate Universal Artificial Intelligence and Self-Play Learning for Games''. Ph.D. thesis, [https://en.wikipedia.org/wiki/University_of_New_South_Wales University of New South Wales], supervisors: [[Kee Siong Ng]], [[Marcus Hutter]], [[Alan Blair]], [[William Uther]], [[John Lloyd]]; [http://jveness.info/publications/veness_phd_thesis_final.pdf pdf]</ref>. Meep is based on the tournament chess engine [[Bodo]], where the hand-crafted [[Evaluation Function|evaluation function]] is replaced by a weighted [https://en.wikipedia.org/wiki/Linear_combination linear combination] of 1812 features. Given a position s, a [https://en.wikipedia.org/wiki/Feature_vector feature vector] Φ(s) can be constructed from the 1812 numeric values of each feature. The majority of these features are binary. Φ(s) is typically sparse, with approximately 100 features active in any given position. Five wellknown, chess specific feature construction concepts, [[Material|material]], [[Piece-Square Tables|piece square tables]], [[Pawn Structure|pawn structure]], [[Mobility|mobility]] and [[King Safety|king safety]] were used to generate the 1812 distinct features. In a training mode with various search frameworks, Meep learns from self-play to adjust the weights of its evaluation function towards the value of the deep search. A tournament mode is later used to verify the [[Playing Strength|strength]] of a trained weight configuration.  </div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>=BootStrap=  </div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>=BootStrap=  </div></td></tr>
</table>
GerdIsenberg
https://www.chessprogramming.org/index.php?title=Meep&diff=4647&oldid=prev
GerdIsenberg at 20:37, 23 June 2018
2018-06-23T20:37:21Z
<p></p>
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<td colspan="2" style="background-color: white; color:black; text-align: center;">Revision as of 20:37, 23 June 2018</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l7" >Line 7:</td>
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<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>=BootStrap=  </div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>=BootStrap=  </div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>In contrast to [[Temporal Difference Learning|temporal difference methods]] such as [[Temporal Difference Learning#TDLeaf|TD-Leaf]] <ref>[[Jonathan Baxter]], [[Andrew Tridgell]], [[Lex Weaver]] ('''1998'''). ''TDLeaf(lambda): Combining Temporal Difference Learning with Game-Tree Search''. [https://www.chatbots.org/journal/australian_journal_of_intelligent_information_processing_systems/ Australian Journal of Intelligent Information Processing Systems], Vol. 5 No. 1, [http://arxiv.org/abs/cs/9901001 arXiv:cs/9901001]</ref> as used in [[KnightCap]] <del class="diffchange diffchange-inline"><ref>[[Jonathan Baxter]], [[Andrew Tridgell]], [[Lex Weaver]] ('''1998''') ''Knightcap: A chess program that learns by combining td(λ) with game-tree search''. Proceedings of the 15th International Conference on Machine Learning</ref> </del>, where the target search is performed at subsequent time-steps, after a real move and response have been played, Meep performs various [https://en.wikipedia.org/wiki/Bootstrap_aggregating bootstrapping] techniques during training, dubbed '''RootStrap''' and '''TreeStrap''', to adjust the weights at every time-step inside either a [[Minimax|minimax]] or [[Alpha-Beta|alpha-beta]] search. With the heuristic evaluation function as linear combination of</div></td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>In contrast to [[Temporal Difference Learning|temporal difference methods]] such as [[Temporal Difference Learning#TDLeaf|TD-Leaf]] <ref>[[Jonathan Baxter]], [[Andrew Tridgell]], [[Lex Weaver]] ('''1998'''). ''TDLeaf(lambda): Combining Temporal Difference Learning with Game-Tree Search''. [https://www.chatbots.org/journal/australian_journal_of_intelligent_information_processing_systems/ Australian Journal of Intelligent Information Processing Systems], Vol. 5 No. 1, [http://arxiv.org/abs/cs/9901001 arXiv:cs/9901001]</ref> as used in [[KnightCap]], where the target search is performed at subsequent time-steps, after a real move and response have been played, Meep performs various [https://en.wikipedia.org/wiki/Bootstrap_aggregating bootstrapping] techniques during training, dubbed '''RootStrap''' and '''TreeStrap''', to adjust the weights at every time-step inside either a [[Minimax|minimax]] or [[Alpha-Beta|alpha-beta]] search. With the heuristic evaluation function as linear combination of</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>[[File:MeepFormula1.jpg|none|text-bottom]]</div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>[[File:MeepFormula1.jpg|none|text-bottom]]</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td></tr>
</table>
GerdIsenberg
https://www.chessprogramming.org/index.php?title=Meep&diff=4646&oldid=prev
GerdIsenberg at 20:17, 23 June 2018
2018-06-23T20:17:16Z
<p></p>
<table class="diff diff-contentalign-left" data-mw="interface">
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<td colspan="2" style="background-color: white; color:black; text-align: center;">Revision as of 20:17, 23 June 2018</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l85" >Line 85:</td>
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<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>* [[Automated Tuning]]</div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>* [[Automated Tuning]]</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>* [[Bodo]]</div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>* [[Bodo]]</div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* [[Alan Blair#Duchess|Duchess]] (Multi-Player Chess Variant)</ins></div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>* [[KnightCap]]</div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>* [[KnightCap]]</div></td></tr>
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</table>
GerdIsenberg
https://www.chessprogramming.org/index.php?title=Meep&diff=4632&oldid=prev
GerdIsenberg: Created page with "'''Home * Engines * Meep''' FILE:Bizarre 1946 volume 3.jpg|border|right|thumb|260px|Strapped woman <ref>Cover of [https://en.wikipedia.org/wiki/Bizarre Bi..."
2018-06-23T16:38:01Z
<p>Created page with "'''<a href="/Main_Page" title="Main Page">Home</a> * <a href="/Engines" title="Engines">Engines</a> * Meep''' FILE:Bizarre 1946 volume 3.jpg|border|right|thumb|260px|Strapped woman <ref>Cover of [https://en.wikipedia.org/wiki/Bizarre Bi..."</p>
<p><b>New page</b></p><div>'''[[Main Page|Home]] * [[Engines]] * Meep'''<br />
<br />
[[FILE:Bizarre 1946 volume 3.jpg|border|right|thumb|260px|Strapped woman <ref>Cover of [https://en.wikipedia.org/wiki/Bizarre Bizarre], Vol. 3 from 1946, depicting a chained woman, and a devil with tailoring tools promising torments due to the wasp-waisted "Fashions of 1946". by [https://commons.wikimedia.org/wiki/Category:John_Willie John Willie], [https://en.wikipedia.org/wiki/Wikimedia_Commons Wikimedia Commons]</ref> ]] <br />
<br />
'''Meep''',<br/><br />
an experimental chess engine as subject of research on [[Learning|machine learning]] techniques and [[Automated Tuning|automated tuning]], written by [[Joel Veness]], supported by [[David Silver]], [[William Uther]], and [[Alan Blair]], as elaborated in their 2009 research paper this page is based on <ref>[[Joel Veness]], [[David Silver]], [[William Uther]], [[Alan Blair]] ('''2009'''). ''[http://papers.nips.cc/paper/3722-bootstrapping-from-game-tree-search Bootstrapping from Game Tree Search]''. [http://jveness.info/publications/nips2009%20-%20bootstrapping%20from%20game%20tree%20search.pdf pdf]</ref> , and in Joel Veness' Ph.D. thesis <ref>[[Joel Veness]] ('''2011'''). ''Approximate Universal Artificial Intelligence and Self-Play Learning for Games''. Ph.D. thesis, [https://en.wikipedia.org/wiki/University_of_New_South_Wales University of New South Wales], supervisors: [[Kee Siong Ng]], [[Marcus Hutter]], [[Alan Blair]], [[William Uther]], [[John Lloyd]]; [http://jveness.info/publications/veness_phd_thesis_final.pdf pdf]</ref> . Meep is based on the [[UCI]] compliant tournament chess engine [[Bodo]], where the hand-crafted [[Evaluation Function|evaluation function]] is replaced by a weighted [https://en.wikipedia.org/wiki/Linear_combination linear combination] of 1812 features. Given a position s, a [https://en.wikipedia.org/wiki/Feature_vector feature vector] Φ(s) can be constructed from the 1812 numeric values of each feature. The majority of these features are binary. Φ(s) is typically sparse, with approximately 100 features active in any given position. Five wellknown, chess specific feature construction concepts, [[Material|material]], [[Piece-Square Tables|piece square tables]], [[Pawn Structure|pawn structure]], [[Mobility|mobility]] and [[King Safety|king safety]] were used to generate the 1812 distinct features. In a training mode with various search frameworks, Meep learns from self-play to adjust the weights of its evaluation function towards the value of the deep search. A tournament mode is later used to verify the [[Playing Strength|strength]] of a trained weight configuration. <br />
<br />
=BootStrap= <br />
In contrast to [[Temporal Difference Learning|temporal difference methods]] such as [[Temporal Difference Learning#TDLeaf|TD-Leaf]] <ref>[[Jonathan Baxter]], [[Andrew Tridgell]], [[Lex Weaver]] ('''1998'''). ''TDLeaf(lambda): Combining Temporal Difference Learning with Game-Tree Search''. [https://www.chatbots.org/journal/australian_journal_of_intelligent_information_processing_systems/ Australian Journal of Intelligent Information Processing Systems], Vol. 5 No. 1, [http://arxiv.org/abs/cs/9901001 arXiv:cs/9901001]</ref> as used in [[KnightCap]] <ref>[[Jonathan Baxter]], [[Andrew Tridgell]], [[Lex Weaver]] ('''1998''') ''Knightcap: A chess program that learns by combining td(λ) with game-tree search''. Proceedings of the 15th International Conference on Machine Learning</ref> , where the target search is performed at subsequent time-steps, after a real move and response have been played, Meep performs various [https://en.wikipedia.org/wiki/Bootstrap_aggregating bootstrapping] techniques during training, dubbed '''RootStrap''' and '''TreeStrap''', to adjust the weights at every time-step inside either a [[Minimax|minimax]] or [[Alpha-Beta|alpha-beta]] search. With the heuristic evaluation function as linear combination of<br />
[[File:MeepFormula1.jpg|none|text-bottom]]<br />
<br />
where Φ(s) is a vector of features of position s, and θ is a parameter vector specifying the weight of each feature in the linear combination, following backup rules are given, using V as backed up value of the minimax or alpha-beta search (left arrow [https://en.wikipedia.org/wiki/Theta theta] (←<span style="vertical-align: super;<br />
font-size: 70%;">''θ''</span>) denotes the operator that updates the heuristic function towards some target value): <br />
<br />
{| class="wikitable"<br />
|-<br />
! Algorithm <br />
! Backup <br />
|-<br />
| TD <br />
| [[File:MeepFormula2.jpg|none|text-bottom]]<br />
|-<br />
| TD-Root <br />
| [[File:MeepFormula3.jpg|none|text-bottom]]<br />
|-<br />
| TD-Leaf <br />
| [[File:MeepFormula4.jpg|none|text-bottom]]<br />
|-<br />
| RootStrap(minimax) <br />
| [[File:MeepFormula5.jpg|none|text-bottom]] <br />
|-<br />
| TreeStrap(minimax) <br />
| [[File:MeepFormula6.jpg|none|text-bottom]] <br />
|-<br />
| TreeStrap(αβ) <br />
| [[File:MeepFormula7.jpg|none|text-bottom]] <br />
|}<br />
<br />
{| <br />
|-<br />
| [[FILE:TDRootAndLeaf.jpg|none|border|text-bottom]] <br />
| [[FILE:MeepStraps.jpg|none|border|text-bottom]] <br />
|-<br />
| TD, TD-Root and TD-Leaf backups <br />
| RootStrap and TreeStrap(minimax) backups <ref>Images cropped from [[Joel Veness]], [[David Silver]], [[William Uther]], [[Alan Blair]] ('''2009'''). ''[http://papers.nips.cc/paper/3722-bootstrapping-from-game-tree-search Bootstrapping from Game Tree Search]''. [http://jveness.info/publications/nips2009%20-%20bootstrapping%20from%20game%20tree%20search.pdf pdf], Figure 1, pp. 2</ref> <br />
|}<br />
<br />
==RootStrap== <br />
RootStrap(minimax) or the identical RootStrap(αβ) adjust the weights by [https://en.wikipedia.org/wiki/Stochastic_gradient_descent stochastic gradient descent] <ref>[https://en.wikipedia.org/wiki/Del Nabla operator from Wikipedia]</ref> on the [https://en.wikipedia.org/wiki/Mean_squared_error squared error] between the [[Evaluation|static evaluation]] and the minimax (or alpha-beta) search value of the [[Root|root]].<br />
<br />
[[File:MeepFormula8.jpg|none|text-bottom]]<br />
<br />
[[File:MeepFormula9.jpg|none|text-bottom]]<br />
<br />
where η is a step size constant.<br />
<br />
==TreeStrap== <br />
TreeStrap(mm) also considers all [[Interior Node|interior nodes]] of the [[Search Tree|search tree]] for the [https://en.wikipedia.org/wiki/Stochastic_gradient_descent stochastic gradient descent] on the [https://en.wikipedia.org/wiki/Mean_squared_error squared error]. The minimax algorithm used for TreeStrap(mm), keeps the entire tree in [[Memory|memory]]. TreeStrap(αβ) applies a generic implementation, that uses only a few enhancements, [[Transposition Table|transposition table]], [[Killer Heuristic|killer]] and [[History Heuristic|history heuristics]], and [[Check Extensions|check extensions]]. Bounds computed by alpha-beta can be exploited by using a one-sided [https://en.wikipedia.org/wiki/Loss_function loss functions]. If the static evaluation is larger than alpha, then it is reduced towards alpha. If the value from the heuristic evaluation is smaller than beta, then it is increased respectively.<br />
<br />
=Results= <br />
A tournament of ~16,000 games of 1 minute per game plus 1 second per move [[Time Management#FischerTime|Fischer time]] between different trained Meep versions and a reference player with randomly initialised weights and arbitrarily assigned rating of 250 was played. Training was previously done by self-play with the same time, using a small opening book to maintain diversity. The target values were determined by at least one ply of full-width search, plus a varying amount of [[Quiescence Search|quiescence search]]. All Elo values are calculated relative to the reference player, the best performance with 95% confidence intervals given <ref>[[Joel Veness]], [[David Silver]], [[William Uther]], [[Alan Blair]] ('''2009'''). ''[http://papers.nips.cc/paper/3722-bootstrapping-from-game-tree-search Bootstrapping from Game Tree Search]''. [http://jveness.info/publications/nips2009%20-%20bootstrapping%20from%20game%20tree%20search.pdf pdf]</ref> :<br />
<br />
{| class="wikitable"<br />
|-<br />
! Algorithm <br />
! Elo <br />
|-<br />
| style="text-align:left;" | Untrained <br />
| style="text-align:right;" | 250 ± 63 <br />
|-<br />
| style="text-align:left;" | TD-Leaf <br />
| style="text-align:right;" | 1068 ± 36 <br />
|-<br />
| style="text-align:left;" | RootStrap(αβ) <br />
| style="text-align:right;" | 1362 ± 59 <br />
|-<br />
| style="text-align:left;" | TreeStrap(mm) <br />
| style="text-align:right;" | 1807 ± 32 <br />
|-<br />
| style="text-align:left;" | TreeStrap(αβ) <br />
| style="text-align:right;" | 2157 ± 31 <br />
|}<br />
<br />
=See also= <br />
* [[Automated Tuning]]<br />
* [[Bodo]]<br />
* [[KnightCap]]<br />
<br />
=Publications= <br />
* [[Joel Veness]], [[David Silver]], [[William Uther]], [[Alan Blair]] ('''2009'''). ''[http://papers.nips.cc/paper/3722-bootstrapping-from-game-tree-search Bootstrapping from Game Tree Search]''. [http://jveness.info/publications/nips2009%20-%20bootstrapping%20from%20game%20tree%20search.pdf pdf] <ref>[http://www.talkchess.com/forum/viewtopic.php?start=0&t=31667 A paper about parameter tuning] by [[Rémi Coulom]], [[CCC]], January 12, 2010</ref><br />
* [[Joel Veness]] ('''2011'''). ''Approximate Universal Artificial Intelligence and Self-Play Learning for Games''. Ph.D. thesis, [https://en.wikipedia.org/wiki/University_of_New_South_Wales University of New South Wales], supervisors: [[Kee Siong Ng]], [[Marcus Hutter]], [[Alan Blair]], [[William Uther]], [[John Lloyd]]; [http://jveness.info/publications/veness_phd_thesis_final.pdf pdf]<br />
* [[István Szita]] ('''2012'''). ''[http://link.springer.com/chapter/10.1007%2F978-3-642-27645-3_17 Reinforcement Learning in Games]''. in [[Marco Wiering]], [http://martijnvanotterlo.nl/ Martijn Van Otterlo] (eds.). ''[https://scholar.google.com/citations?view_op=view_citation&hl=en&user=xVas0I8AAAAJ&citation_for_view=xVas0I8AAAAJ:abG-DnoFyZgC Reinforcement learning: State-of-the-art]''. [http://link.springer.com/book/10.1007/978-3-642-27645-3 Adaptation, Learning, and Optimization, Vol. 12], [https://en.wikipedia.org/wiki/Springer_Science%2BBusiness_Media Springer]<br />
<br />
=Forum Posts= <br />
* [http://www.talkchess.com/forum/viewtopic.php?start=0&t=31667 A paper about parameter tuning] by [[Rémi Coulom]], [[CCC]], January 12, 2010<br />
: [http://www.talkchess.com/forum/viewtopic.php?start=0&t=31667&start=25 Re: A paper about parameter tuning] by [[Joel Veness]], [[CCC]], January 15, 2010<br />
: [http://www.talkchess.com/forum/viewtopic.php?start=0&t=31667&start=27 Re: A paper about parameter tuning] by [[Joel Veness]], [[CCC]], January 15, 2010<br />
<br />
=External Links= <br />
* [http://videolectures.net/nips09_veness_bfg/ Bootstrapping from Game Tree Search], video presentation by [[Joel Veness]], from [http://videolectures.net/ VideoLectures - exchange ideas & share knowledge], December 2009<br />
* [https://en.wikipedia.org/wiki/Meep Meep from Wikipedia]<br />
* [http://de.urbandictionary.com/define.php?term=meep Urban Dictionary: meep]<br />
* [https://en.wikipedia.org/wiki/Bootstrapping Bootstrapping from Wikipedia]<br />
* [https://en.wikipedia.org/wiki/Bootstrapping_%28disambiguation%29 Bootstrapping (disambiguation) from Wikipedia]<br />
* [https://en.wikipedia.org/wiki/Bootstrap_aggregating Bootstrap aggregating from Wikipedia]<br />
* [https://en.wikipedia.org/wiki/Strapping Strapping from Wikipedia]<br />
* [https://de.wikipedia.org/wiki/Strapse Strapse from Wikipedia.de] (German)<br />
: [https://en.wikipedia.org/wiki/Garter_%28stockings%29#Garter_belts Wearing suspenders or garter belts from Wikipedia]<br />
* [[Videos#VolkerKriegel|Volker Kriegel]] - Three Or Two In One, [http://www.discogs.com/Volker-Kriegel-Lift/release/726875 Lift!], 1973, [https://en.wikipedia.org/wiki/YouTube YouTube] Video<br />
: feat: [[Videos#EberhardWeber|Eberhard Weber]], [[Videos#JohnMarshall|John Marshall]], [https://en.wikipedia.org/wiki/Stan_Sulzmann Stan Sulzmann], [https://en.wikipedia.org/wiki/John_Taylor_%28jazz%29 John Taylor], [https://de.wikipedia.org/wiki/Cees_See Cees See], [[Videos#ZbigniewSeifert|Zbigniew Seifert]]<br />
: {{#evu:https://www.youtube.com/watch?v=neBBmEAHQoQ|alignment=left|valignment=top}}<br />
<br />
=References= <br />
<references /><br />
<br />
'''[[Engines|Up one level]]'''</div>
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