Author: Juergen Wolf
Date: 12:10:16 08/14/03
According to the publisher of MTD (Plaat,A Minimax Algorithm faster than NegaScout, http://theory.lcs.mit.edu/~plaat/mtdf.html) , MTD is supposed to be better than Negascout. As the article stresses the value of transposition-tables in MTD , i wondering whether the comparision is done against Negascout without using transposition tables (question 1) . Also i'm wondering whether the author provided a formal proof of his statement (question 2). Just in case he compared MTD against Negascout with transposition-table, I assume he did not provide a formal proof, as he provides some implementation tips , just in case it turns out that Negascout is still better. Nevertheless i think its an interesting idea worth to be tested . I like the simplicity of MTD. I read some previous threads and there seems to be some programs where MTD is not of any benefit. Is it correct to assume that those programs are using IID (question 3). My understanding is that IID is not useful in zero-window search and is used just in case no move was found in the transposition-table. Did somebody ever compare Negascout+transposition+IID vs MTD (question 4)? My thought is that IID might provide sufficient "compensation". My program so far used a window of +/- 0.2pawns for the 1st search, in case of a fail high i redo another search with a window of 1.2 pawns and in case this still fails high i'm using the max-window. I implemented MTD (work of minutes and is working) and intend to do some extensive benchmarks. Plaat also mention that the MTD-grain is important. My program has an eval-grain/stepsize of 1/1000 pawn. Is there a benchmark comparing success of MTD (using different settings of step-size) wrt to grain of eval-function (question 5). For example if i have a grain of 1/1000 in eval - function , is a stepsize of 10 , 20 , 40 (1000 points = 1 pawn) better than "worst case" 1 ? I read that in case of MTD its important to store lower-bound AND upper-bound. So far my program just stores one value. Did somebody compare these two approaches (question 6)? Wrt to transposition table i read statements that using a move from a fail-low search should not be taken as preferred move. What are the general experiences on this (please describe feature set of program, question 7) ? A read a long time ago an article proposing , in case that a Zero-window search provides a fail high (a better move found than the best-move-so-far), it might be worthwhile not to do a full research just to find the exact value. In case another move beats the best-value , both moves have to explored agained to decide whether move 2 or 3 is better. Are there any statistic/experiences available (question 7)? i intend to make those benchmarks with my own program in order to decide which is the best setting for my program, but would like to compare my results with the "rest of the world" ( or set my expectation right) kind regards juergen wolf
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