2 papers
cs.LG2025
Observational Learning with a Budget
Shuo Wu, Pawan Poojary, Randall Berry
We consider a model of Bayesian observational learning in which a sequence of agents receives a private signal about an underlying binary state of the world. Each agent makes a dec…
cs.LG2024
When to Trust Your Data: Enhancing Dyna-Style Model-Based Reinforcement Learning With Data Filter
Yansong Li, Zeyu Dong, Ertai Luo +3
Reinforcement learning (RL) algorithms can be divided into two classes: model-free algorithms, which are sample-inefficient, and model-based algorithms, which suffer from model bia…