Enter Your Reply The Comment You're Replying To H. G. Muller wrote on Thu, Oct 23, 2008 09:36 AM UTC:M. Winther | Muller, to get piece values at ~3% exactitude you would need to | presuppose that piece values are static properties. But they are | really changeable with regard to tactical and strategical context. Not necessarily. I always measure piece values in a well-defined context, e.g. opening values, end-game values. Piece values are by definition strategic quantities, I avoid starting in tactical positions, and for an accurate measurement I average over many non-tactical initial positions with similar peiece makeup. This usually gives quite consistent results, when you keep the number of pieces and the total value of present material approximately constant. (i.e. the difference of the performance of two diffent pieces is hardly dependend on the details of the makeup of the opponent or its allies.) That piece values change as the board empties, because. e.g., Rooks get more freedom of movement and Cannons can find fewer platforms, is something that can be measured separately. If the piece values found for the various qualitatively different situations differ, you can try to add material-interaction terms in the evaluation. (The best known example of such a term in normal chess is one proportional to the product of the number of Bishops and number of Pawns, making the effective B-N difference dependent on the number of Pawns.) | This means that you would probably have to foresee the future in, | say, ten moves in order to get a ~3% exactitude. I am not sure what you mean by 'forsee the future'. By playing out the game until checkmate or legal draw, I effectively make a Monte-Carlo sampilng of all plausible futures. But it is important that the sample is generated under conditions of reasonabe tactical accuracy, or you would not be sampling a representative set of realistic positions, which then would distort the results. | One obvious example is XiangQi. Chinese Chess masters are hard pressed | to reveal the relative values of pieces. Those pieces which are | completely lousy, like the elephant and the mandarin, are sometimes | very valuable while they provide protection for the general, function | as screens for the cannon, or can block enemy pieces. So, in a certain | context they become very valuable. I have not built an engine to play Xiangqi yet (I am in the preliminary design stage now of an engine that could play Shogi, Chess and Xiangi with arbitrary Chess men on boards upto 10x10.) So I have not done any measurements for tuning. Quite possibly the material-interaction terms in Xiangqi are much larger than in Chess, due to the peculiar capture mode of the Cannon and the restricted access pieces have to the board. It seems to me that the effects you describe can be described reaconably well by cross-product terms of number of Cannons and number of other pieces. This transcends pure piece values, but can be measured just as easily. | Ten moves later, the elephant or mandarin is useless. Probably, in | chinese chess, only a human is capable of evaluating a piece. Such a fast change is usually tactical, and then has little to do with strategic piece values. Unles the strategic situation completely changed in those ten moves, e.g. because all heavy material got traded, or all hoppers got traded. But in that case such differences can easily be expressed by terms that are proportional to the amount of heavy material / number of hoppers. I doubt if Humans could do this job better than computers. This is why I would like to build a Xiangqi engine, so that I could do similar tests on piece values as I am doing now for Chess. Edit Form You may not post a new comment, because ItemID Zillions and GC does not match any item.