[ Help | Earliest Comments | Latest Comments ][ List All Subjects of Discussion | Create New Subject of Discussion ][ List Earliest Comments Only For Pages | Games | Rated Pages | Rated Games | Subjects of Discussion ]Single Comment Aberg variation of Capablanca's Chess. Different setup and castling rules. (10x8, Cells: 80) [All Comments] [Add Comment or Rating]H.G.Muller wrote on 2008-05-01 UTCI still can't see the point you are tring to make. If piece values cannot be used to predict outcomes of games, they would be useless in the first place. Why would you want to be an exchange or a piece ahead, if it might as frequently mean you are losing as that you are winning? Fact is that I OBSERVE that the piece values I have given below do statistically predict the outcome of games with good precision. If, according to you, that should not be the case, than apparently you are wrong. If, according to you, that is not what 'good' piece values should do, than that satisfactorily explains why you would consider your set of piece values, which would cause whatever entity that uses them to play by to lose consistently, in your eyes can still be 'good', and further discussion could add nothing to that. What you say about opponent modelling doesn't have anything to do with piece values. Precisely knowing the limitations of your opponent allows you to play a theoretically losing strategy (e.g. doing bad trades) in order to set a trap. In general, this is a losing strategy, as in practice one cannot be sufficiently sure about where the opponent's horizon will be. So it will backfire more often than not. And the datasets that are analyzed by me or Kaufman are not dominated by players engaging in such opponent modelling. I can be certain of that for my own data, as I wrote the engine(s) generating it myself. So I know they only attempt theoretically optimal play that would work against any opponent.