Author: Bas Hamstra
Date: 19:46:33 01/12/01
Within a few days I will put a new version of Tao 5.5 on Frank's web site. There have been several small improvements, resulting in an ELO improvement of exactly 50.00 points. The main difference is that it uses evaluation learning based on Temporal Difference. With all parameters set to zero it quickly learns how to improve the most important eval terms, and play better chess. In my opinion however, it is not able to set all terms to optimal values within a reasonable amount of time. Judge it yourself, you can let it learn from zero, or you can turn learning of and tweak the weights manually. So far, it seems best to start with a good guess and hand-tweak the few terms it does not seem to learn (or learns too slow). Having learning turned on has no performance penalty. The main differences with the previous version are: - Temporal Difference learning (can be scaled from 1000 to zero = off) - More accurate repetion detection - Better tactics (290 WAC within 5 sec) - Eval changes to let it play more interestingly and actively - Eval parameters user settable - More accurate PV's (less half PV's that end in the hash table) - Improved search efficiency - Some changes and additions to the evaluation I have not hand tuned the eval weights for a long time, like in the previous version. Therefore the eval is sometimes over-optimistic and maybe not totally balanced. But still, IMO, it plays very interesting attacking active REAL chess. I have not had time to test it at very long time controls. Have fun! Bas.
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