Parametric SPIBB and game-based pruning reduce the data required for safe policy improvement by up to two orders of magnitude, while SMT-based pruning is shown to be computationally infeasible.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.AI 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Data-Efficient Safe Policy Improvement Using Parametric Structure
Parametric SPIBB and game-based pruning reduce the data required for safe policy improvement by up to two orders of magnitude, while SMT-based pruning is shown to be computationally infeasible.