← Authors

Hongyao Tang

22 papers · 2019–2025 · 5 conferences · across top CS/AI conferences

Achievements

πŸ—ΊοΈ Taxonomy Completionist (36) 🌍 Conference Polyglot (5) πŸƒ Academic Marathon (6) 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (11) 🀝 Dynamic Duo (18) πŸ‘‘ Triple Crown πŸ† Grand Slam πŸ”¬ Deep Specialist (10) 🧬 Topic Evolution πŸš€ Conference Pioneer ⚑ Prolific Year (5) πŸ—ƒοΈ Keyword Collector (84) πŸ”₯ Unstoppable (7) πŸ’Ž Century Club (22)

Conferences

ICML (7) AAAI (6) NIPS (4) IJCAI (3) ICLR (2)

Top co-authors

Jianye Hao (18) YAN ZHENG (9) Zhaopeng Meng (8) Pengyi Li (7) Chen Chen (5) Wulong Liu (5) Dong Li (4) Yaodong Yang (3) Zhen Wang (3) Xian Fu (3)

Keywords

deep reinforcement learning (7) multi-agent reinforcement learning (5) representation learning (4) policy learning (3) reinforcement learning (3) policy optimization (3) offline reinforcement learning (2) proximal policy optimization (2) evolutionary algorithm (2) contrastive learning (2) value estimation (2) neural network optimization (1) autonomous driving (1) progressive learning (1) knowledge distillation (1) value function estimation (1) function approximation (1) value function approximation (1) value function (1) mutual information (1)

Papers

Mitigating Plasticity Loss in Continual Reinforcement Learning by Reducing Churn ICML 2025
R*: Efficient Reward Design via Reward Structure Evolution and Parameter Alignment Optimization with Large Language Models ICML 2025
Designing Biological Sequences without Prior Knowledge Using Evolutionary Reinforcement Learning AAAI 2024
The Ladder in Chaos: Improving Policy Learning by Harnessing the Parameter Evolving Path in A Low-dimensional Space NIPS 2024
EvoRainbow: Combining Improvements in Evolutionary Reinforcement Learning for Policy Search ICML 2024
Value-Evolutionary-Based Reinforcement Learning ICML 2024
Improving Deep Reinforcement Learning by Reducing the Chain Effect of Value and Policy Churn NIPS 2024
RACE: Improve Multi-Agent Reinforcement Learning with Representation Asymmetry and Collaborative Evolution ICML 2023
ERL-Re$^2$: Efficient Evolutionary Reinforcement Learning with Shared State Representation and Individual Policy Representation ICLR 2023
Reining Generalization in Offline Reinforcement Learning via Representation Distinction NIPS 2023
PAnDR: Fast Adaptation to New Environments from Offline Experiences via Decoupling Policy and Environment Representations IJCAI 2022
What about Inputting Policy in Value Function: Policy Representation and Policy-Extended Value Function Approximator AAAI 2022
HyAR: Addressing Discrete-Continuous Action Reinforcement Learning via Hybrid Action Representation ICLR 2022
PMIC: Improving Multi-Agent Reinforcement Learning with Progressive Mutual Information Collaboration ICML 2022
An Efficient Transfer Learning Framework for Multiagent Reinforcement Learning NIPS 2021
Foresee then Evaluate: Decomposing Value Estimation with Latent Future Prediction AAAI 2021
Towards Effective Context for Meta-Reinforcement Learning: an Approach based on Contrastive Learning AAAI 2021
Addressing Action Oscillations through Learning Policy Inertia AAAI 2021
Q-value Path Decomposition for Deep Multiagent Reinforcement Learning ICML 2020
KoGuN: Accelerating Deep Reinforcement Learning via Integrating Human Suboptimal Knowledge IJCAI 2020
An Optimal Rewiring Strategy for Cooperative Multiagent Social Learning AAAI 2019
Deep Multi-Agent Reinforcement Learning with Discrete-Continuous Hybrid Action Spaces IJCAI 2019