A translation method converts finite-state-controller policies for POMDPs into a decision-tree-plus-Mealy-machine form that is typically smaller and more explainable, with further simplifications for attractor-based policies.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.AI 1years
2024 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Explainable Representation of Finite-Memory Policies for POMDPs using Decision Trees
A translation method converts finite-state-controller policies for POMDPs into a decision-tree-plus-Mealy-machine form that is typically smaller and more explainable, with further simplifications for attractor-based policies.