42 research outputs found

    Chess endgame knowledge advances

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    This review of recent developments starts with the publication of Harold van der Heijden's Study Database Edition IV, John Nunn's second trilogy on the endgame, and a range of endgame tables (EGTs) to the DTC, DTZ and DTZ50 metrics. It then summarises data-mining work by Eiko Bleicher and Guy Haworth in 2010. This used CQL and pgn2fen to find some 3,000 EGT-faulted studies in the database above, and the Type A (value-critical) and Type B-DTM (DTM-depth-critical) zugzwangs in the mainlines of those studies. The same technique was used to mine Chessbase's BIG DATABASE 2010 to identify Type A/B zugzwangs, and to identify the pattern of value-concession and DTM-depth concession in sub-7-man play

    Strategies for Constrained Optimisation

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    The latest 6-man chess endgame results confirm that there are many deep forced mates beyond the 50-move rule. Players with potential wins near this limit naturally want to avoid a claim for a draw: optimal play to current metrics does not guarantee feasible wins or maximise the chances of winning against fallible opposition. A new metric and further strategies are defined which support players’ aspirations and improve their prospects of securing wins in the context of a k-move rule

    3-5-man mutual zugzwangs in chess

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    This note reports the work of Wirth and Karrer in twin-sourcing all mutual zugzwang positions, mzugs, in 2-5-man endgames. This paper tabulates the mzug statistical data, gives examples of maximal mzugs and refers to a chess endgame website where further data is to be found

    Depth by The Rule

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    This note corrects a previous treatment of algorithms for the metric DTR, Depth by the Rule

    6-man chess solved

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    Eugene Nalimov has completed the computation of a set of endgame tables for 6-man chess, and independently, Marc Bourzutschky has completed tables for 3-3 chess and for 4-2 chess where Black is not just ‘KP’. The ICGA salutes both achievements and looks ahead

    Student projects: plagiarism and assessment

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    Within the Information Technology degree programme of the University of Reading, the students undertake a major project in their final year. The module is both a hurdle to an honours degree and significant in terms of assessment weighting. The two year history so far has shown that bad citation and plagiarism are issues, and in one case called for the due referral of a project report. In the light of experience to date, we are focusing firstly on plagiarism prevention, giving generic advice on report writing and citation practice, and secondly on detection. In the longer term, I believe we need to reflect on what capabilities we should be creating in our undergraduates and therefore what and how we should be assessing them

    Gentlemen, stop your engines!

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    For fifty years, computer chess has pursued an original goal of Artificial Intelligence, to produce a chess-engine to compete at the highest level. The goal has arguably been achieved, but that success has made it harder to answer questions about the relative playing strengths of man and machine. The proposal here is to approach such questions in a counter-intuitive way, handicapping or stopping-down chess engines so that they play less well. The intrinsic lack of man-machine games may be side-stepped by analysing existing games to place computer engines as accurately as possible on the FIDE ELO scale of human play. Move-sequences may also be assessed for likelihood if computer-assisted cheating is suspected

    3-5-Man chess data

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    This reports the work of Karrer and Wirth in identifying percentage results and, respectively, the Depth to Mate (DTM) and Depth to Conversion (DTC) data in all 2-5-man chess endgames

    Database Engines for Geographical Information Systems

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    Our ability to identify, acquire, store, enquire on and analyse data is increasing as never before, especially in the GIS field. Technologies are becoming available to manage a wider variety of data and to make intelligent inferences on that data. The mainstream arrival of large-scale database engines is not far away. The experience of using the first such products tells us that they will radically change data management in the GIS field

    Deepest Chess Win Revisited

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    An examination of the deepest win in KRNKNN in the context of Ken Thompson's results
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