Zhang-Wei Hong | DeepAI

DeepAI AI Chat

Featured Co-authors

Jan Peters
143 publications
Tao Chen
134 publications
Ali Jadbabaie
66 publications
Min Sun
65 publications
Ming-Yu Liu
59 publications
Aviv Tamar
56 publications
Pulkit Agrawal
52 publications
Joni Pajarinen
34 publications
Martin Rinard
32 publications
Romain Laroche
29 publications
Chun-Yi Lee
27 publications

∙ 07/24/2023

Parallel Q-Learning: Scaling Off-policy Reinforcement Learning under Massively Parallel Simulation

Reinforcement learning is time-consuming for complex tasks due to the ne...

0 Zechu Li, et al. ∙

∙ 07/11/2023

Neuro-Inspired Efficient Map Building via Fragmentation and Recall

Animals and robots navigate through environments by building and refinin...

0 Jaedong Hwang, et al. ∙

∙ 07/06/2023

TGRL: An Algorithm for Teacher Guided Reinforcement Learning

Learning from rewards (i.e., reinforcement learning or RL) and learning ...

0 Idan Shenfeld, et al. ∙

∙ 06/22/2023

Harnessing Mixed Offline Reinforcement Learning Datasets via Trajectory Weighting

Most offline reinforcement learning (RL) algorithms return a target poli...

0 Zhang-Wei Hong, et al. ∙

∙ 04/27/2023

Decentralized Inference via Capability Type Structures in Cooperative Multi-Agent Systems

This work studies the problem of ad hoc teamwork in teams composed of ag...

0 Charles Jin, et al. ∙

∙ 11/14/2022

Redeeming Intrinsic Rewards via Constrained Optimization

State-of-the-art reinforcement learning (RL) algorithms typically use ra...

5 Eric Chen, et al. ∙

∙ 10/17/2022

Model Predictive Control via On-Policy Imitation Learning

In this paper, we leverage the rapid advances in imitation learning, a t...

0 Kwangjun Ahn, et al. ∙

∙ 03/29/2022

Topological Experience Replay

State-of-the-art deep Q-learning methods update Q-values using state tra...

7 Zhang-Wei Hong, et al. ∙

∙ 03/14/2022

Stubborn: A Strong Baseline for Indoor Object Navigation

We present a strong baseline that surpasses the performance of previousl...

0 Haokuan Luo, et al. ∙

∙ 05/30/2021

Reducing the Deployment-Time Inference Control Costs of Deep Reinforcement Learning Agents via an Asymmetric Architecture

Deep reinforcement learning (DRL) has been demonstrated to provide promi...

0 Chin-Jui Chang, et al. ∙

∙ 07/16/2020

Mixture of Step Returns in Bootstrapped DQN

The concept of utilizing multi-step returns for updating value functions...

0 Po-Han Chiang, et al. ∙

∙ 02/01/2020

Periodic Intra-Ensemble Knowledge Distillation for Reinforcement Learning

Off-policy ensemble reinforcement learning (RL) methods have demonstrate...

1 Zhang-Wei Hong, et al. ∙

∙ 08/15/2019

Model-based Lookahead Reinforcement Learning

Model-based Reinforcement Learning (MBRL) allows data-efficient learning...

0 Zhang-Wei Hong, et al. ∙

∙ 06/26/2018

Adversarial Exploration Strategy for Self-Supervised Imitation Learning

We present an adversarial exploration strategy, a simple yet effective i...

0 Zhang-Wei Hong, et al. ∙

∙ 02/13/2018

Diversity-Driven Exploration Strategy for Deep Reinforcement Learning

Efficient exploration remains a challenging research problem in reinforc...

0 Zhang-Wei Hong, et al. ∙

∙ 02/01/2018

Virtual-to-Real: Learning to Control in Visual Semantic Segmentation

Collecting training data from the physical world is usually time-consumi...

0 Zhang-Wei Hong, et al. ∙

∙ 12/21/2017

A Deep Policy Inference Q-Network for Multi-Agent Systems

We present DPIQN, a deep policy inference Q-network that targets multi-a...

0 Zhang-Wei Hong, et al. ∙

∙ 03/08/2017

Tactics of Adversarial Attack on Deep Reinforcement Learning Agents

We introduce two tactics to attack agents trained by deep reinforcement ...

0 Yen-Chen Lin, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world