Author: guy haworth
Date: 08:30:57 01/01/01
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Don Beal did a paper in ICCA_J some time ago to evaluate the values of the pieces by TD Learning. Various 'runs' came out with different values ... the surprise for me was the strength of the B over the N. With the P at '1', I think the Q came out ~9.5 and the R about 4.5. Other experiments have shown that the learning process is so inefficient as to be arguable ineffective. Michael Buro favours Bayesian statistical analysis of features and I agree ... if you can find the features to analyse An experiment that I proposed in ICCA_J in 1998 (v21.4) is to take an established linear evaluation function as the start-point for a 2-level artificial neural network and see how the ANN's parameters evolve. In other games, investigators have replaced a single Linear Weighted Sum by multiple LWSs. There is an argument that line pieces grow in value, e.g., as more space becomes available.
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