Six-man Oracle Survey, 1

This is a list in GBR order of existing 6-man endgame tables (EGTs) created by Nalimov (DTM, Distance to Mate) or Thompson (DTC, Distance to Conversion).

Haworth's Law

The maximum 'Depth to Mate' (DTM(k)) data for k-man chess, k = 3-7, is now available: log(maxDTM(k)) demonstrates quasi-linear behaviour. This note predicts maxDTM for 8- to 10-man chess and the two-sigma distributions around these figures. 'Haworth's Law' is the conjecture that maxDTM will continue to demonstrate this behaviour for some time to come. The supporting datafile is a pgn of maxDTM positions, each having a DTM-minimaxing line of play from it to 'mate'.

Chess Endgame News

This paper notes FIDE's 75-move rule (9.6b) and suggests some implications. It reviews two endgame-table initiatives associated with the 50-move rule. One is Huntington's mainly sub-6-man multi-valued DTM50 EGTs implemented in HASKELL. The other is Ronald de Man's WDL' and DTZ50' EGTs which introduce a 5-way evaluation of positions, and ascribe a depth to decisive positions which are not 50-move-rule wins or losses. There is also some first detail about the Lomonosov '7-man DTM EGT' team, and comments on reactions to 'Haworth's Law'.

Depth to mate and the 50-move rule

The most popular endgame tables (EGTs) documenting ‘DTM’ Depth to Mate in chess endgames are those of Eugene Nalimov but these do not recognise the FIDE 50-move rule ‘50mr’. This paper marks the creation by the first author of EGTs for sub-6-man (s6m) chess and beyond which give DTM as affected by the ply count pc. The results are put into the context of previous work recognising the 50mr and are compared with the original unmoderated DTM results. The work is also notable for being the first EGT generation work to use the functional programming language HASKELL.

The potential of flood forecasting using a variable-resolution global Digital Terrain Model and flood extents from Synthetic Aperture Radar images

A basic data requirement of a river flood inundation model is a Digital Terrain Model (DTM) of the reach being studied. The scale at which modeling is required determines the accuracy required of the DTM. For modeling floods in urban areas, a high resolution DTM such as that produced by airborne LiDAR (Light Detection And Ranging) is most useful, and large parts of many developed countries have now been mapped using LiDAR. In remoter areas, it is possible to model flooding on a larger scale using a lower resolution DTM, and in the near future the DTM of choice is likely to be that derived from the TanDEM-X Digital Elevation Model (DEM). A variable-resolution global DTM obtained by combining existing high and low resolution data sets would be useful for modeling flood water dynamics globally, at high resolution wherever possible and at lower resolution over larger rivers in remote areas. A further important data resource used in flood modeling is the flood extent, commonly derived from Synthetic Aperture Radar (SAR) images. Flood extents become more useful if they are intersected with the DTM, when water level observations (WLOs) at the flood boundary can be estimated at various points along the river reach. To illustrate the utility of such a global DTM, two examples of recent research involving WLOs at opposite ends of the spatial scale are discussed. The first requires high resolution spatial data, and involves the assimilation of WLOs from a real sequence of high resolution SAR images into a flood model to update the model state with observations over time, and to estimate river discharge and model parameters, including river bathymetry and friction. The results indicate the feasibility of such an Earth Observation-based flood forecasting system. The second example is at a larger scale, and uses SAR-derived WLOs to improve the lower-resolution TanDEM-X DEM in the area covered by the flood extents. The resulting reduction in random height error is significant.