3 papers
cs.RO2023
Resolving uncertainty on the fly: Modeling adaptive driving behavior as active inference
Johan Engström, Ran Wei, Anthony McDonald +3
Understanding adaptive human driving behavior, in particular how drivers manage uncertainty, is of key importance for developing simulated human driver models that can be used in t…
cs.LG2023
A Unified View on Solving Objective Mismatch in Model-Based Reinforcement Learning
Ran Wei, Nathan Lambert, Anthony McDonald +2
Model-based Reinforcement Learning (MBRL) aims to make agents more sample-efficient, adaptive, and explainable by learning an explicit model of the environment. While the capabilit…
cs.LG2023
A Bayesian Approach to Robust Inverse Reinforcement Learning
Ran Wei, Siliang Zeng, Chenliang Li +3
We consider a Bayesian approach to offline model-based inverse reinforcement learning (IRL). The proposed framework differs from existing offline model-based IRL approaches by perf…