Qiang Fu

Affiliations:
  • Tencent AI Lab, Shenzhen, China


According to our database1, Qiang Fu authored at least 52 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Dynamics-Adaptive Continual Reinforcement Learning via Progressive Contextualization.
IEEE Trans. Neural Networks Learn. Syst., October, 2024

Diverse Policies Recovering via Pointwise Mutual Information Weighted Imitation Learning.
CoRR, 2024

Hokoff: Real Game Dataset from Honor of Kings and its Offline Reinforcement Learning Benchmarks.
CoRR, 2024

Reaching Consensus in Cooperative Multi-Agent Reinforcement Learning with Goal Imagination.
CoRR, 2024

More Agents Is All You Need.
CoRR, 2024

Enhance Reasoning for Large Language Models in the Game Werewolf.
CoRR, 2024

Affordable Generative Agents.
CoRR, 2024

Enhancing Human Experience in Human-Agent Collaboration: A Human-Centered Modeling Approach Based on Positive Human Gain.
CoRR, 2024

Automatically designing counterfactual regret minimization algorithms for solving imperfect-information games.
Artif. Intell., 2024

Minimizing Weighted Counterfactual Regret with Optimistic Online Mirror Descent.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Dynamic Discounted Counterfactual Regret Minimization.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Maximum Entropy Heterogeneous-Agent Reinforcement Learning.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Towards Offline Opponent Modeling with In-context Learning.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Enhancing Human Experience in Human-Agent Collaboration: A Human-Centered Modeling Approach Based on Positive Human Gain.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Not All Tasks Are Equally Difficult: Multi-Task Deep Reinforcement Learning with Dynamic Depth Routing.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
RLTF: Reinforcement Learning from Unit Test Feedback.
Trans. Mach. Learn. Res., 2023

Not All Tasks Are Equally Difficult: Multi-Task Reinforcement Learning with Dynamic Depth Routing.
CoRR, 2023

Diversity from Human Feedback.
CoRR, 2023

Maximum Entropy Heterogeneous-Agent Mirror Learning.
CoRR, 2023

Future-conditioned Unsupervised Pretraining for Decision Transformer.
CoRR, 2023

Sample Dropout: A Simple yet Effective Variance Reduction Technique in Deep Policy Optimization.
CoRR, 2023

Revisiting Estimation Bias in Policy Gradients for Deep Reinforcement Learning.
CoRR, 2023

Automatic Grouping for Efficient Cooperative Multi-Agent Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Policy Space Diversity for Non-Transitive Games.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Hokoff: Real Game Dataset from Honor of Kings and its Offline Reinforcement Learning Benchmarks.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Robust and Opponent-Aware League Training Method for StarCraft II.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Multi-objective Optimization-based Selection for Quality-Diversity by Non-surrounded-dominated Sorting.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Future-conditioned Unsupervised Pretraining for Decision Transformer.
Proceedings of the International Conference on Machine Learning, 2023

Opponent-Limited Online Search for Imperfect Information Games.
Proceedings of the International Conference on Machine Learning, 2023

Quality-Similar Diversity via Population Based Reinforcement Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Curriculum-based Co-design of Morphology and Control of Voxel-based Soft Robots.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Towards Effective and Interpretable Human-Agent Collaboration in MOBA Games: A Communication Perspective.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

PreCo: Enhancing Generalization in Co-Design of Modular Soft Robots via Brain-Body Pre-Training.
Proceedings of the Conference on Robot Learning, 2023

Sequential Cooperative Multi-Agent Reinforcement Learning.
Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

RLogist: Fast Observation Strategy on Whole-Slide Images with Deep Reinforcement Learning.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Supervised Learning Achieves Human-Level Performance in MOBA Games: A Case Study of Honor of Kings.
IEEE Trans. Neural Networks Learn. Syst., 2022

Revisiting Discrete Soft Actor-Critic.
CoRR, 2022

Honor of Kings Arena: an Environment for Generalization in Competitive Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

JueWu-MC: Playing Minecraft with Sample-efficient Hierarchical Reinforcement Learning.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Greedy when Sure and Conservative when Uncertain about the Opponents.
Proceedings of the International Conference on Machine Learning, 2022

Actor-Critic Policy Optimization in a Large-Scale Imperfect-Information Game.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Speedup Training Artificial Intelligence for Mahjong via Reward Variance Reduction.
Proceedings of the IEEE Conference on Games, CoG 2022, Beijing, 2022

AutoCFR: Learning to Design Counterfactual Regret Minimization Algorithms.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Which Heroes to Pick? Learning to Draft in MOBA Games With Neural Networks and Tree Search.
IEEE Trans. Games, 2021


Learning Diverse Policies in MOBA Games via Macro-Goals.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

MapGo: Model-Assisted Policy Optimization for Goal-Oriented Tasks.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Combining Tree Search and Action Prediction for State-of-the-Art Performance in DouDiZhu.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Boosting Offline Reinforcement Learning with Residual Generative Modeling.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

2020
Towards Playing Full MOBA Games with Deep Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Mastering Complex Control in MOBA Games with Deep Reinforcement Learning.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2018
Hierarchical Macro Strategy Model for MOBA Game AI.
CoRR, 2018


  Loading...