8 papers
Adaptive Finite-Budget Training for CVaR Risk-Aware Q-Learning
Yifan Wu, Junjie Lei, Wenjie Huang
Risk-aware Q-learning (RaQL) provides a model-free, two-timescale estimator for dynamic risk objectives, but its finite-budget behavior remains fragile: fixed inner-loop hyperparam…
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…
Reachable Sets-based Trajectory Planning Combining Reinforcement Learning and iLQR
Wenjie Huang, Yang Li, Shijie Yuan +3
The driving risk field is applicable to more complex driving scenarios, providing new approaches for safety decision-making and active vehicle control in intricate environments. Ho…
Model and Reinforcement Learning for Markov Games with Risk Preferences
Wenjie Huang, Pham Viet Hai, William B. Haskell
We motivate and propose a new model for non-cooperative Markov game which considers the interactions of risk-aware players. This model characterizes the time-consistent dynamic "ri…
Data-driven satisficing measure and ranking
Wenjie Huang
We propose an computational framework for real-time risk assessment and prioritizing for random outcomes without prior information on probability distributions. The basic model is…
Preference Elicitation and Robust Optimization with Multi-Attribute Quasi-Concave Choice Functions
William B. Haskell, Wenjie Huang, Huifu Xu
Decision maker's preferences are often captured by some choice functions which are used to rank prospects. In this paper, we consider ambiguity in choice functions over a multi-att…