papers

Publications (40)

cs.AI2020

KoGuN: Accelerating Deep Reinforcement Learning via Integrating Human Suboptimal Knowledge

Peng Zhang, Jianye Hao, Weixun Wang +4

cs.LG2021

Uncertainty-aware Low-Rank Q-Matrix Estimation for Deep Reinforcement Learning

Tong Sang, Hongyao Tang, Jianye Hao +2

cs.LG2023

The Ladder in Chaos: A Simple and Effective Improvement to General DRL Algorithms by Policy Path Trimming and Boosting

Hongyao Tang, Min Zhang, Jianye Hao

cs.RO2026

Embodied-R1.5: Evolving Physical Intelligence via Embodied Foundation Models

Yifu Yuan, Yaoting Huang, Xianze Yao +20

cs.LG2025

Scaling DRL for Decision Making: A Survey on Data, Network, and Training Budget Strategies

Yi Ma, Hongyao Tang, Chenjun Xiao +4

cs.LG2024

Improving Deep Reinforcement Learning by Reducing the Chain Effect of Value and Policy Churn

Hongyao Tang, Glen Berseth

cs.MA2020

Q-value Path Decomposition for Deep Multiagent Reinforcement Learning

Yaodong Yang, Jianye Hao, Guangyong Chen +5

cs.LG2025

Squeeze the Soaked Sponge: Efficient Off-policy Reinforcement Finetuning for Large Language Model

Jing Liang, Hongyao Tang, Yi Ma +5

cs.LG2020

MGHRL: Meta Goal-generation for Hierarchical Reinforcement Learning

Haotian Fu, Hongyao Tang, Jianye Hao +2

cs.NE2026

Bridging Evolutionary Algorithms and Reinforcement Learning: A Comprehensive Survey on Hybrid Algorithms

Pengyi Li, Jianye Hao, Hongyao Tang +3

cs.AI2023

Exploration in Deep Reinforcement Learning: From Single-Agent to Multiagent Domain

Jianye Hao, Tianpei Yang, Hongyao Tang +5

cs.LG2020

Towards Effective Context for Meta-Reinforcement Learning: an Approach based on Contrastive Learning

Haotian Fu, Hongyao Tang, Jianye Hao +4

cs.LG2021

Foresee then Evaluate: Decomposing Value Estimation with Latent Future Prediction

Hongyao Tang, Jianye Hao, Guangyong Chen +6

cs.LG2019

Disentangling Dynamics and Returns: Value Function Decomposition with Future Prediction

Hongyao Tang, Jianye Hao, Guangyong Chen +4

cs.MA2021

An Efficient Transfer Learning Framework for Multiagent Reinforcement Learning

Tianpei Yang, Weixun Wang, Hongyao Tang +9

cs.LG2026

The Rank and Gradient Lost in Non-stationarity: Sample Weight Decay for Mitigating Plasticity Loss in Reinforcement Learning

Zihao Wu, Hongyao Tang, Yi Ma +3

cs.LG2019

Deep Multi-Agent Reinforcement Learning with Discrete-Continuous Hybrid Action Spaces

Haotian Fu, Hongyao Tang, Jianye Hao +3

cs.LG2022

HyAR: Addressing Discrete-Continuous Action Reinforcement Learning via Hybrid Action Representation

Boyan Li, Hongyao Tang, Yan Zheng +5

cs.NE2023

ERL-Re: Efficient Evolutionary Reinforcement Learning with Shared State Representation and Individual Policy Representation

Jianye Hao, Pengyi Li, Hongyao Tang +3

cs.LG2025

Efficient Morphology-Aware Policy Transfer to New Embodiments

Michael Przystupa, Hongyao Tang, Martin Jagersand +4

cs.MA2023

PMIC: Improving Multi-Agent Reinforcement Learning with Progressive Mutual Information Collaboration

Pengyi Li, Hongyao Tang, Tianpei Yang +8

cs.LG2022

Towards A Unified Policy Abstraction Theory and Representation Learning Approach in Markov Decision Processes

Min Zhang, Hongyao Tang, Jianye Hao +1

cs.LG2022

PAnDR: Fast Adaptation to New Environments from Offline Experiences via Decoupling Policy and Environment Representations

Tong Sang, Hongyao Tang, Yi Ma +5

cs.MA2018

An Optimal Rewiring Strategy for Reinforcement Social Learning in Cooperative Multiagent Systems

Hongyao Tang, Li Wang, Zan Wang +2

cs.AI2026

RoboPIN: Grounded Embodied Reasoning via Pinned Chain-of-Thought

Yaoting Huang, Yifu Yuan, Linqi Han +6

cs.RO2026

Embodied-R1: Reinforced Embodied Reasoning for General Robotic Manipulation

Yifu Yuan, Haiqin Cui, Yaoting Huang +7

cs.MA2025

Dual Ensembled Multiagent Q-Learning with Hypernet Regularizer

Yaodong Yang, Guangyong Chen, Hongyao Tang +3

cs.LG2026

The Mirage of Optimizing Training Policies: Monotonic Inference Policies as the Real Objective for LLM Reinforcement Learning

Jing Liang, Hongyao Tang, Yi Ma +9

cs.LG2021

What About Inputing Policy in Value Function: Policy Representation and Policy-extended Value Function Approximator

Hongyao Tang, Zhaopeng Meng, Jianye Hao +9

cs.LG2026

Reformulate LLM Reinforcement Learning for Efficient Training under Black-box Discrepancy

Jiashun Liu, Runze Liu, Xu Wan +3

cs.RO2025

MUVLA: Learning to Explore Object Navigation via Map Understanding

Peilong Han, Fan Jia, Min Zhang +5

cs.LG2025

Mitigating Plasticity Loss in Continual Reinforcement Learning by Reducing Churn

Hongyao Tang, Johan Obando-Ceron, Pablo Samuel Castro +2

cs.RO2025

Embodied Arena: A Comprehensive, Unified, and Evolving Evaluation Platform for Embodied AI

Fei Ni, Min Zhang, Pengyi Li +34

cs.LG2019

Hierarchical Deep Multiagent Reinforcement Learning with Temporal Abstraction

Hongyao Tang, Jianye Hao, Tangjie Lv +8

cs.LG2022

State-Aware Proximal Pessimistic Algorithms for Offline Reinforcement Learning

Chen Chen, Hongyao Tang, Yi Ma +4

cs.MA2020

Qatten: A General Framework for Cooperative Multiagent Reinforcement Learning

Yaodong Yang, Jianye Hao, Ben Liao +4

cs.AI2024

MFE-ETP: A Comprehensive Evaluation Benchmark for Multi-modal Foundation Models on Embodied Task Planning

Min Zhang, Xian Fu, Jianye Hao +5

cs.RO2026

ForceFlow: Learning to Feel and Act via Contact-Driven Flow Matching

Shuoheng Zhang, Yifu Yuan, Hongyao Tang +7

cs.LG2025

Can We Optimize Deep RL Policy Weights as Trajectory Modeling?

Hongyao Tang

cs.LG2021

Addressing Action Oscillations through Learning Policy Inertia

Chen Chen, Hongyao Tang, Jianye Hao +2