On Mon, May 22, 2017 at 11:27 AM, Erik van der Werf < erikvanderw...@gmail.com> wrote:
> On Mon, May 22, 2017 at 10:08 AM, Gian-Carlo Pascutto <g...@sjeng.org> > wrote: >> >> ... This heavy pruning >> by the policy network OTOH seems to be an issue for me. My program has >> big tactical holes. > > > Do you do any hard pruning? My engines (Steenvreter,Magog) always had a > move predictor (a.k.a. policy net), but I never saw the need to do hard > pruning. Steenvreter uses the predictions to set priors, and it is very > selective, but with infinite simulations eventually all potentially > relevant moves will get sampled. > > Oh, haha, after reading Brian's post I guess I misunderstood :-) Anyway, LMR seems like a good idea, but last time I tried it (in Migos) it did not help. In Magog I had some good results with fractional depth reductions (like in Realization Probability Search), but it's a long time ago and the engines were much weaker then...
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