Efficiency

Prior-dependent analysis of posterior sampling reinforcement learning with function approximation

Has implications on how the integration of prior knowledge enhances the efficiency of RL agents without extensive online exploration.

Yingru Li, Zhi-Quan Luo

HyperAgent - A Simple, Efficient, Scalable and Provable RL Framework

Practically and provably efficient RL under resource constraints!

Mar 23, 2024 1:30 PM Rice University

Yingru LI

HyperAgent - A Simple, Efficient and Scalable RL Framework for Complex Environments

Practically and provably efficient RL under resource constraints!

Jan 13, 2024 1:20 PM Daoyuan Building

Yingru LI

HyperAgent - A Simple, Efficient and Scalable RL Framework for Complex Environments

Towards AGI for Humanity through Efficient Reinforcement Learning

Addressing efficiency chanllenge in RL by HyperFQI algorithm

Oct 21, 2023 2:30 PM Teaching B Building

Yingru LI

Towards AGI for Humanity through Efficient Reinforcement Learning

HyperDQN: A Randomized Exploration Method for Deep Reinforcement Learning

TL;DR: We design a practical randomized exploration method to address the sample efficiency issue in online reinforcement learning.

Ziniu Li, Yingru Li* (corresponding), Yushun Zhang, Tong Zhang, Zhi-Quan Luo

HyperDQN - Randomized Exploration for Deep Reinforcement Learning

Dec 14, 2021 12:00 AM NeurIPS 2021

Yingru LI

HyperDQN - Randomized Exploration for Deep Reinforcement Learning