1 citations · 2 across the 8 of their papers we have counts for
4 papers · 1 filter
Feature-Based Belief Aggregation for Partially Observable Markov Decision Problems
Yuchao Li, Kim Hammar, Dimitri Bertsekas
We consider a finite-state partially observable Markov decision problem (POMDP) with an infinite horizon and a discounted cost, and we propose a new method for computing a cost fun…
Adaptive Network Security Policies via Belief Aggregation and Rollout
Kim Hammar, Yuchao Li, Tansu Alpcan +2
Evolving security vulnerabilities and shifting operational conditions require frequent updates to network security policies. These updates include adjustments to incident response…
An Error Bound for Aggregation in Approximate Dynamic Programming
Yuchao Li, Dimitri Bertsekas
We consider a general aggregation framework for discounted finite-state infinite horizon dynamic programming (DP) problems. It defines an aggregate problem whose optimal cost funct…
Semilinear Dynamic Programming: Analysis, Algorithms, and Certainty Equivalence Properties
Yuchao Li, Dimitri Bertsekas
We consider a broad class of dynamic programming (DP) problems that involve a partially linear structure and some positivity properties in their system equation and cost function.…