3 papers
math.OC2026
History-Dependent Recursive Preferences in Markov Decision Processes
William B. Haskell
In finite horizon dynamic programming with history-dependent preferences, the relevant state may be the entire realized history, even when the physical state is Markov. This paper…
math.OC2026
Robust Data-Driven Quasiconcave Optimization
Jian Wu, William B. Haskell, Wenjie Huang +1
We investigate a data-driven quasiconcave maximization problem where information about the objective function is limited to a finite sample of data points. We begin by defining an…
q-fin.RM2025
Efficiently Computing the Quasiconcave Envelope with Incomplete Information
Jian Wu, William B. Haskell, Wenjie Huang +1
In this paper, we study the approximation of an unknown quasiconcave function based on limited partial information. Available information includes lower bounds on the values of the…