If you know in a playout that the best reply has to be one of only a handful of options (e.g. in a semeai), non-zero probabilities for all of those moves plus LGRF should be a nice way of making the search adapt. But whenever you make the conditions more specific, be aware that you will get fewer samples per condition, and you need lots of samples to be able to count on good replies staying in the table longer than bad replies.
OK, got it. thanks.
If you could find an efficient way of combining LGRF with local patterns, I would see some potential. I couldn't get it to run fast enough.
Yes, I can. In Erica, I can incrementally update patterns up to size 5. Combining LGRF with local patterns is in my list to try tomorrow. Thanks for your informative suggestions.
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