4 papers
Dynamic Programming for Value-at-Risk Markov Decision Processes in Continuous Spaces
Xian Chen, Erick Delage, Weikai Wang
Value-at-Risk (VaR) is a widely adopted quantile-based risk measure in practice, yet incorporating VaR objectives into Markov decision processes (VaR MDPs) remains a longstanding c…
Online Policy Evaluation for MDPs with Dynamic UBSR Measures
Weikai Wang, Erick Delage
Developing efficient function-approximation methods for policy evaluation is a fundamental challenge in risk-aware reinforcement learning. Existing approaches either focus on restr…
Planning and Learning in Average Risk-aware MDPs
Weikai Wang, Erick Delage
For continuing tasks, average cost Markov decision processes have well-documented value and can be solved using efficient algorithms. However, it explicitly assumes that the agent…
Enhancing EEG Signal Generation through a Hybrid Approach Integrating Reinforcement Learning and Diffusion Models
Yang An, Yuhao Tong, Weikai Wang +1
The present study introduces an innovative approach to the synthesis of Electroencephalogram (EEG) signals by integrating diffusion models with reinforcement learning. This integra…