From 49056db67690f38d9d8d3c44b4bd130f591b4643 Mon Sep 17 00:00:00 2001 From: Nikolaj Bjorner Date: Tue, 12 Aug 2025 14:58:58 -0700 Subject: [PATCH] add notes on parameter tuning Signed-off-by: Nikolaj Bjorner --- PARALLEL_PROJECT_NOTES.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/PARALLEL_PROJECT_NOTES.md b/PARALLEL_PROJECT_NOTES.md index 7716a2a24..b60263e4e 100644 --- a/PARALLEL_PROJECT_NOTES.md +++ b/PARALLEL_PROJECT_NOTES.md @@ -140,7 +140,7 @@ The initial values of reward functions is fixed (to 1) and the initial values of * The batch manager maintains a set of candidate parameters $CP = \{ (P_1, r_1), \ldots, (P_n, r_n) \}$. * A worker thread picks up a parameter $P_i$ from $CP$ from the batch manager. * It picks one or more parameter settings within $P_i$ whose mutation function have non-zero reward functions and applies a mutation. -* It then runs with a bounded set of cubes. +* It then runs with a batch of cubes. * It measures the reward for the new parameter setting based in number of cubes, cube depth, number of timeouts, and completions with number of conflicts. * If the new reward is an improvement over $(P_i, r_i)$ it inserts the new parameter setting $(P_i', r_i')$ into the batch manager. * The batch manager discards the worst parameter settings keeping the top $K$ ($K = 5$) parameter settings.