The paper defines the ambiguity premium Δ_ε(x) as the gap between pessimistic and optimistic upper-level values over ε-optimal follower responses and provides bounds plus a screening workflow to trace robustness-efficiency frontiers in bilevel problems.
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AGILS is an alternating gradient algorithm for bilevel optimization that uses Moreau envelope reformulation to handle inexact lower-level solves, with convergence to stationary points proven under stated assumptions.
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A Diagnostic Framework for Implementation Risk in Bilevel Decision Problems: The Ambiguity Premium and the Robustness--Efficiency Frontier
The paper defines the ambiguity premium Δ_ε(x) as the gap between pessimistic and optimistic upper-level values over ε-optimal follower responses and provides bounds plus a screening workflow to trace robustness-efficiency frontiers in bilevel problems.
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Alternating Gradient-Type Algorithm for Bilevel Optimization with Inexact Lower-Level Solutions via Moreau Envelope-based Reformulation
AGILS is an alternating gradient algorithm for bilevel optimization that uses Moreau envelope reformulation to handle inexact lower-level solves, with convergence to stationary points proven under stated assumptions.