The SSDF Chess Engine Rating List, 2019-02
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Videos Bearbeiten Im Überblick: Sieben Aktuelle VIDEOSCHNITT Werkzeuge Für Den Videoschnitt
Miller: Texttool-Allrounder Wego: Schicke Wetter-COMMUNITY-EDITIONManjaro i3: Arch-Derivat mit bereitet CSVs optimal auf S. 54 App für die Konsole S. 44 Tiling-Window-Manager S. 48 Frei kopieren und beliebig weiter verteilen ! 03.2016 03.2016 Guter Schnitt für Bild und Ton, eindrucksvolle Effekte, perfektes Mastering VIDEOSCHNITT Videos bearbeiten Im Überblick: Sieben aktuelle VIDEOSCHNITT Werkzeuge für den Videoschnitt unter Linux im Direktvergleich S. 10 • Veracrypt • Wego • Wego • Veracrypt • Pitivi & OpenShot: Einfach wie noch nie – die neue Generation der Videoschnitt-Werkzeuge S. 20 Lightworks: So kitzeln Sie optimale Ergebnisse aus der kostenlosen Free-Version heraus S. 26 Verschlüsselte Daten sicher verstecken S. 64 Glaubhafte Abstreitbarkeit: Wie Sie mit dem Truecrypt-Nachfolger • SQLiteStudio Stellarium Synology RT1900ac Veracrypt wichtige Daten unauffindbar in Hidden Volumes verbergen Stellarium erweitern S. 32 Workshop SQLiteStudio S. 78 Eigene Objekte und Landschaften Die komfortable Datenbankoberfläche ins virtuelle Planetarium einbinden für Alltagsprogramme auf dem Desktop Top-Distris • Anydesk • Miller PyChess • auf zwei Heft-DVDs ANYDESK • MILLER • PYCHESS • STELLARIUM • VERACRYPT • WEGO • • WEGO • VERACRYPT • STELLARIUM • PYCHESS • MILLER • ANYDESK EUR 8,50 EUR 9,35 sfr 17,00 EUR 10,85 EUR 11,05 EUR 11,05 2 DVD-10 03 www.linux-user.de Deutschland Österreich Schweiz Benelux Spanien Italien 4 196067 008502 03 Editorial Old and busted? Jörg Luther Chefredakteur Sehr geehrte Leserinnen und Leser, viele kleinere, innovative Distributionen seit einem Jahrzehnt kommen Desktop- Immer öfter stellen wir uns aber die haben damit erst gar nicht angefangen und Notebook-Systeme nur noch mit Frage, ob es wirklich noch Sinn ergibt, oder sparen es sich schon lange. Open- 64-Bit-CPUs, sodass sich die Zahl der moderne Distributionen überhaupt Suse verzichtet seit Leap 42.1 darauf; das 32-Bit-Systeme in freier Wildbahn lang- noch als 32-Bit-Images beizulegen. -
Development of Games for Users with Visual Impairment Czech Technical University in Prague Faculty of Electrical Engineering
Development of games for users with visual impairment Czech Technical University in Prague Faculty of Electrical Engineering Dina Chernova January 2017 Acknowledgement I would first like to thank Bc. Honza Had´aˇcekfor his valuable advice. I am also very grateful to my supervisor Ing. Daniel Nov´ak,Ph.D. and to all participants that were involved in testing of my application for their precious time. I must express my profound gratitude to my loved ones for their support and continuous encouragement throughout my years of study. This accomplishment would not have been possible without them. Thank you. 5 Declaration I declare that I have developed this thesis on my own and that I have stated all the information sources in accordance with the methodological guideline of adhering to ethical principles during the preparation of university theses. In Prague 09.01.2017 Author 6 Abstract This bachelor thesis deals with analysis and implementation of mobile application that allows visually impaired people to play chess on their smart phones. The application con- trol is performed using special gestures and text{to{speech engine as a sound accompanier. For human against computer game mode I have used currently the best game engine called Stockfish. The application is developed under Android mobile platform. Keywords: chess; visually impaired; Android; Bakal´aˇrsk´apr´acese zab´yv´aanal´yzoua implementac´ımobiln´ıaplikace, kter´aumoˇzˇnuje zrakovˇepostiˇzen´ymlidem hr´atˇsachy na sv´emsmartphonu. Ovl´ad´an´ıaplikace se prov´ad´ı pomoc´ıspeci´aln´ıch gest a text{to{speech enginu pro zvukov´edoprov´azen´ı.V reˇzimu ˇclovˇek versus poˇc´ıtaˇcjsem pouˇzilasouˇcasnˇenejlepˇs´ıhern´ıengine Stockfish. -
(2021), 2814-2819 Research Article Can Chess Ever Be Solved Na
Turkish Journal of Computer and Mathematics Education Vol.12 No.2 (2021), 2814-2819 Research Article Can Chess Ever Be Solved Naveen Kumar1, Bhayaa Sharma2 1,2Department of Mathematics, University Institute of Sciences, Chandigarh University, Gharuan, Mohali, Punjab-140413, India [email protected], [email protected] Article History: Received: 11 January 2021; Accepted: 27 February 2021; Published online: 5 April 2021 Abstract: Data Science and Artificial Intelligence have been all over the world lately,in almost every possible field be it finance,education,entertainment,healthcare,astronomy, astrology, and many more sports is no exception. With so much data, statistics, and analysis available in this particular field, when everything is being recorded it has become easier for team selectors, broadcasters, audience, sponsors, most importantly for players themselves to prepare against various opponents. Even the analysis has improved over the period of time with the evolvement of AI, not only analysis one can even predict the things with the insights available. This is not even restricted to this,nowadays players are trained in such a manner that they are capable of taking the most feasible and rational decisions in any given situation. Chess is one of those sports that depend on calculations, algorithms, analysis, decisions etc. Being said that whenever the analysis is involved, we have always improvised on the techniques. Algorithms are somethingwhich can be solved with the help of various software, does that imply that chess can be fully solved,in simple words does that mean that if both the players play the best moves respectively then the game must end in a draw or does that mean that white wins having the first move advantage. -
Chess Tests: Basic Suite, Positions 16-20
Chess Tests: Basic Suite, Positions 16-20 (c) Valentin Albillo, 2020 Last update: 14/01/98 See the Notes on Problem Solving 16.- Z. Franco vs. J. Gil FEN: rbb1N1k1/pp1n1ppp/8/2Pp4/3P4/4P3/P1Q2PPq/R1BR1K2/ b Black to play and win: 1. ... Nd7xc5 2. Qc5 Qh1+ 3. Ke2 Bg4+ 4. f3 Results Program CPU/Mhz Hash table Move Value Plys/Max Time Notes Chess Genius 1.0 P100 320 Kb Nd7xc5 +0.39 5/17 00:00:17 sees little value Chess Genius 1.0 P100 320 Kb Nd7xc5 +1.72 7/19 00:04:49 sees to 4. f3 Pentium Pro 200 MHz 24 Mb + 16 Mb Nd7xc5 +2.14 10/19 00:01:20 seen at 14s Crafty 12.6 P6 ? Nd7xc5 +1.181 11/17 00:01:46 see notes Crafty 13.3 Pentium Pro 200 Mhz ? Nd7xc5 +2.46 9 00:03:05 Chess Master 5500 Pentium Pro 200 Mhz 10 Mb Nd7xc5 +2.65 6 00:01:24 seen at 0:00, +0.00 MChess Pro 5.0 Notes: Using Chess Genius 1.0, both searches find the correct Knight's sacrifice. The 5-ply one, however, does not see it's full value, while the 7-ply search, though 16 times slower, correctly predicts the next 6 plies of the actual game, finding the move nearly two pawns worth. Crafty 12.6 finds the correct sacrifice too, though it needs to search to 10 ply, instead of the 7 plies required by CG1.0, but its better hardware makes for the shortest time. -
Draft – Not for Circulation
A Gross Miscarriage of Justice in Computer Chess by Dr. Søren Riis Introduction In June 2011 it was widely reported in the global media that the International Computer Games Association (ICGA) had found chess programmer International Master Vasik Rajlich in breach of the ICGA‟s annual World Computer Chess Championship (WCCC) tournament rule related to program originality. In the ICGA‟s accompanying report it was asserted that Rajlich‟s chess program Rybka contained “plagiarized” code from Fruit, a program authored by Fabien Letouzey of France. Some of the headlines reporting the charges and ruling in the media were “Computer Chess Champion Caught Injecting Performance-Enhancing Code”, “Computer Chess Reels from Biggest Sporting Scandal Since Ben Johnson” and “Czech Mate, Mr. Cheat”, accompanied by a photo of Rajlich and his wife at their wedding. In response, Rajlich claimed complete innocence and made it clear that he found the ICGA‟s investigatory process and conclusions to be biased and unprofessional, and the charges baseless and unworthy. He refused to be drawn into a protracted dispute with his accusers or mount a comprehensive defense. This article re-examines the case. With the support of an extensive technical report by Ed Schröder, author of chess program Rebel (World Computer Chess champion in 1991 and 1992) as well as support in the form of unpublished notes from chess programmer Sven Schüle, I argue that the ICGA‟s findings were misleading and its ruling lacked any sense of proportion. The purpose of this paper is to defend the reputation of Vasik Rajlich, whose innovative and influential program Rybka was in the vanguard of a mid-decade paradigm change within the computer chess community. -
Download Source Engine for Pc Free Download Source Engine for Pc Free
download source engine for pc free Download source engine for pc free. Completing the CAPTCHA proves you are a human and gives you temporary access to the web property. What can I do to prevent this in the future? If you are on a personal connection, like at home, you can run an anti-virus scan on your device to make sure it is not infected with malware. If you are at an office or shared network, you can ask the network administrator to run a scan across the network looking for misconfigured or infected devices. Another way to prevent getting this page in the future is to use Privacy Pass. You may need to download version 2.0 now from the Chrome Web Store. Cloudflare Ray ID: 67a0b2f3bed7f14e • Your IP : 188.246.226.140 • Performance & security by Cloudflare. Download source engine for pc free. Completing the CAPTCHA proves you are a human and gives you temporary access to the web property. What can I do to prevent this in the future? If you are on a personal connection, like at home, you can run an anti-virus scan on your device to make sure it is not infected with malware. If you are at an office or shared network, you can ask the network administrator to run a scan across the network looking for misconfigured or infected devices. Another way to prevent getting this page in the future is to use Privacy Pass. You may need to download version 2.0 now from the Chrome Web Store. Cloudflare Ray ID: 67a0b2f3c99315dc • Your IP : 188.246.226.140 • Performance & security by Cloudflare. -
Distributional Differences Between Human and Computer Play at Chess
Multidisciplinary Workshop on Advances in Preference Handling: Papers from the AAAI-14 Workshop Human and Computer Preferences at Chess Kenneth W. Regan Tamal Biswas Jason Zhou Department of CSE Department of CSE The Nichols School University at Buffalo University at Buffalo Buffalo, NY 14216 USA Amherst, NY 14260 USA Amherst, NY 14260 USA [email protected] [email protected] Abstract In our case the third parties are computer chess programs Distributional analysis of large data-sets of chess games analyzing the position and the played move, and the error played by humans and those played by computers shows the is the difference in analyzed value from its preferred move following differences in preferences and performance: when the two differ. We have run the computer analysis (1) The average error per move scales uniformly higher the to sufficient depth estimated to have strength at least equal more advantage is enjoyed by either side, with the effect to the top human players in our samples, depth significantly much sharper for humans than computers; greater than used in previous studies. We have replicated our (2) For almost any degree of advantage or disadvantage, a main human data set of 726,120 positions from tournaments human player has a significant 2–3% lower scoring expecta- played in 2010–2012 on each of four different programs: tion if it is his/her turn to move, than when the opponent is to Komodo 6, Stockfish DD (or 5), Houdini 4, and Rybka 3. move; the effect is nearly absent for computers. The first three finished 1-2-3 in the most recent Thoresen (3) Humans prefer to drive games into positions with fewer Chess Engine Competition, while Rybka 3 (to version 4.1) reasonable options and earlier resolutions, even when playing was the top program from 2008 to 2011. -
The TCEC19 Computer Chess Superfinal: a Perspective
The TCEC19 Computer Chess Superfinal: a Perspective GM Matthew Sadler1 London, UK 1 THE TCEC19 PREMIER DIVISION Season 19’s Premier Division was a gathering of the usual suspects but one participant was not quite what it seemed! STOCKFISH – mighty in Season 18 – had become STOCKFISH NNUE and there was great anticipation of what the added self-learning component to STOCKFISH’s evaluation would mean for STOCKFISH’s strength. In my own engine matches (on much weaker hardware and faster time controls) played from many types of positions, STOCKFISH NNUE had looked extremely impressive against ‘old-fashioned’ STOCKFISH CLASSICAL. Most surprising to me was that STOCKFISH NNUE defended even better than STOCKFISH CLASSICAL which is not a particular strength of self-learning systems. I just wondered whether at long time controls making STOCKFISH ‘think like an NN’ would blunt the destructive power that makes it so formidable. I also had high hopes for ALLIESTEIN which had performed so impressively in the end-of-season-18 bonus competitions. As it turned out, DivP also had a familiar outcome as STOCKFISH – after a slow start – and a resurgent LEELA forged ahead and dominated the race for the SuperFinal spots. LEELA kept pace for quite a while but a loss to STOCKFISH and a late STOCKFISH surge created a clear gap between first and second. ALLIESTEIN finished a disappointing third, playing solidly but without sparkle. STOOFVLEES did what only it can do, mixing fine games with mini-disasters! The relegation battle was intense with four engines – KOMODO, SCORPIONN, FIRE AND ETHEREAL - in constant danger. -
Extended Null-Move Reductions
Extended Null-Move Reductions Omid David-Tabibi1 and Nathan S. Netanyahu1,2 1 Department of Computer Science, Bar-Ilan University, Ramat-Gan 52900, Israel [email protected], [email protected] 2 Center for Automation Research, University of Maryland, College Park, MD 20742, USA [email protected] Abstract. In this paper we review the conventional versions of null- move pruning, and present our enhancements which allow for a deeper search with greater accuracy. While the conventional versions of null- move pruning use reduction values of R ≤ 3, we use an aggressive re- duction value of R = 4 within a verified adaptive configuration which maximizes the benefit from the more aggressive pruning, while limiting its tactical liabilities. Our experimental results using our grandmaster- level chess program, Falcon, show that our null-move reductions (NMR) outperform the conventional methods, with the tactical benefits of the deeper search dominating the deficiencies. Moreover, unlike standard null-move pruning, which fails badly in zugzwang positions, NMR is impervious to zugzwangs. Finally, the implementation of NMR in any program already using null-move pruning requires a modification of only a few lines of code. 1 Introduction Chess programs trying to search the same way humans think by generating “plausible” moves dominated until the mid-1970s. By using extensive chess knowledge at each node, these programs selected a few moves which they consid- ered plausible, and thus pruned large parts of the search tree. However, plausible- move generating programs had serious tactical shortcomings, and as soon as brute-force search programs such as Tech [17] and Chess 4.x [29] managed to reach depths of 5 plies and more, plausible-move generating programs fre- quently lost to brute-force searchers due to their tactical weaknesses. -
Algorithmic Progress in Six Domains
MIRI MACHINE INTELLIGENCE RESEARCH INSTITUTE Algorithmic Progress in Six Domains Katja Grace MIRI Visiting Fellow Abstract We examine evidence of progress in six areas of algorithms research, with an eye to understanding likely algorithmic trajectories after the advent of artificial general intelli- gence. Many of these areas appear to experience fast improvement, though the data are often noisy. For tasks in these areas, gains from algorithmic progress have been roughly fifty to one hundred percent as large as those from hardware progress. Improvements tend to be incremental, forming a relatively smooth curve on the scale of years. Grace, Katja. 2013. Algorithmic Progress in Six Domains. Technical report 2013-3. Berkeley, CA: Machine Intelligence Research Institute. Last modified December 9, 2013. Contents 1 Introduction 1 2 Summary 2 3 A Few General Points 3 3.1 On Measures of Progress . 3 3.2 Inputs and Outputs . 3 3.3 On Selection . 4 4 Boolean Satisfiability (SAT) 5 4.1 SAT Solving Competition . 5 4.1.1 Industrial and Handcrafted SAT Instances . 6 Speedup Distribution . 6 Two-Year Improvements . 8 Difficulty and Progress . 9 4.1.2 Random SAT Instances . 11 Overall Picture . 11 Speedups for Individual Problem Types . 11 Two-Year Improvements . 11 Difficulty and Progress . 14 4.2 João Marques-Silva’s Records . 14 5 Game Playing 17 5.1 Chess . 17 5.1.1 The Effect of Hardware . 17 5.1.2 Computer Chess Ratings List (CCRL) . 18 5.1.3 Swedish Chess Computer Association (SSDF) Ratings . 19 Archived Versions . 19 Wikipedia Records . 20 SSDF via ChessBase 2003 . 20 5.1.4 Chess Engine Grand Tournament (CEGT) Records . -
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Move Similarity Analysis in Chess Programs
Move similarity analysis in chess programs D. Dailey, A. Hair, M. Watkins Abstract In June 2011, the International Computer Games Association (ICGA) disqual- ified Vasik Rajlich and his Rybka chess program for plagiarism and breaking their rules on originality in their events from 2006-10. One primary basis for this came from a painstaking code comparison, using the source code of Fruit and the object code of Rybka, which found the selection of evaluation features in the programs to be almost the same, much more than expected by chance. In his brief defense, Rajlich indicated his opinion that move similarity testing was a superior method of detecting misappropriated entries. Later commentary by both Rajlich and his defenders reiterated the same, and indeed the ICGA Rules themselves specify move similarity as an example reason for why the tournament director would have warrant to request a source code examination. We report on data obtained from move-similarity testing. The principal dataset here consists of over 8000 positions and nearly 100 independent engines. We comment on such issues as: the robustness of the methods (upon modifying the experimental conditions), whether strong engines tend to play more similarly than weak ones, and the observed Fruit/Rybka move-similarity data. 1. History and background on derivative programs in computer chess Computer chess has seen a number of derivative programs over the years. One of the first was the incident in the 1989 World Microcomputer Chess Cham- pionship (WMCCC), in which Quickstep was disqualified due to the program being \a copy of the program Mephisto Almeria" in all important areas.