Generalizes the Tsitsiklis-van Roy error bound for aggregation in discounted DP to soft and feature-based schemes.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
years
2025 2verdicts
UNVERDICTED 2representative citing papers
Combines particle filtering, feature-based aggregation, and rollout to produce scalable network security policies with theoretical guarantees that adapt quickly to model changes.
citing papers explorer
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An Error Bound for Aggregation in Approximate Dynamic Programming
Generalizes the Tsitsiklis-van Roy error bound for aggregation in discounted DP to soft and feature-based schemes.
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Adaptive Network Security Policies via Belief Aggregation and Rollout
Combines particle filtering, feature-based aggregation, and rollout to produce scalable network security policies with theoretical guarantees that adapt quickly to model changes.