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Parallel Bayesian Network Structure Learning
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| add query subset and superset inference (single agent, K=1) (ablation) | GGSL-style local-to-global learning · ALARM (1000 samples) | total function calls to BNStructLearn: 1418 -> 369 (about 3-4x fewer) | Helped |
| add parallel agents (2 to 5 synchronous) with subset/superset inference | PSL · ALARM (1000 samples) | mean function calls per agent: mean calls fall from 369 (K=1) to 205.5 (K=2), 154.0 (K=3), 112.0 (K=4), 100.6 (K=5) | Helped |
| increase number of synchronous agents | PSL · ALARM (1000 samples) | total function calls to BNStructLearn: 369 (K=1) to 411, 462, 448, 503 for K=2..5 | Mixed |
| higher exploitation probability p in target selection (2 agents) (ablation) | PSL · ALARM (1000 samples) | total function calls to BNStructLearn: 499 at p=0.1 to 393 at p=0.9 | Helped |
| higher exploitation probability p in target selection (2 agents) (ablation) | PSL · ALARM (1000 samples) | BDeu change vs GGSL: +20.8 at p=0.1 and +305.3 at p=0.7, but -385.8 at p=0.9 | Mixed |
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