Optimal deterministic policies for LDST-robust MDPs are NP-hard even in a two-stage, single-deviation reward case, and transition uncertainty is Sigma_2^p-hard, but a 1/(5+epsilon)-approximation exists for the two-stage case.
Robust markov decision p rocesses: Beyond rectangularity
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Robust Deterministic Policies for Markov Decision Processes under Budgeted Uncertainty
Optimal deterministic policies for LDST-robust MDPs are NP-hard even in a two-stage, single-deviation reward case, and transition uncertainty is Sigma_2^p-hard, but a 1/(5+epsilon)-approximation exists for the two-stage case.