Alert button
Picture for Xiaotian Hao

Xiaotian Hao

Alert button

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

Mar 16, 2022
Pengyi Li, Hongyao Tang, Tianpei Yang, Xiaotian Hao, Tong Sang, Yan Zheng, Jianye Hao, Matthew E. Taylor, Zhen Wang

Figure 1 for PMIC: Improving Multi-Agent Reinforcement Learning with Progressive Mutual Information Collaboration
Figure 2 for PMIC: Improving Multi-Agent Reinforcement Learning with Progressive Mutual Information Collaboration
Figure 3 for PMIC: Improving Multi-Agent Reinforcement Learning with Progressive Mutual Information Collaboration
Figure 4 for PMIC: Improving Multi-Agent Reinforcement Learning with Progressive Mutual Information Collaboration
Viaarxiv icon

API: Boosting Multi-Agent Reinforcement Learning via Agent-Permutation-Invariant Networks

Mar 10, 2022
Xiaotian Hao, Weixun Wang, Hangyu Mao, Yaodong Yang, Dong Li, Yan Zheng, Zhen Wang, Jianye Hao

Figure 1 for API: Boosting Multi-Agent Reinforcement Learning via Agent-Permutation-Invariant Networks
Figure 2 for API: Boosting Multi-Agent Reinforcement Learning via Agent-Permutation-Invariant Networks
Figure 3 for API: Boosting Multi-Agent Reinforcement Learning via Agent-Permutation-Invariant Networks
Figure 4 for API: Boosting Multi-Agent Reinforcement Learning via Agent-Permutation-Invariant Networks
Viaarxiv icon

SEIHAI: A Sample-efficient Hierarchical AI for the MineRL Competition

Nov 17, 2021
Hangyu Mao, Chao Wang, Xiaotian Hao, Yihuan Mao, Yiming Lu, Chengjie Wu, Jianye Hao, Dong Li, Pingzhong Tang

Figure 1 for SEIHAI: A Sample-efficient Hierarchical AI for the MineRL Competition
Figure 2 for SEIHAI: A Sample-efficient Hierarchical AI for the MineRL Competition
Figure 3 for SEIHAI: A Sample-efficient Hierarchical AI for the MineRL Competition
Figure 4 for SEIHAI: A Sample-efficient Hierarchical AI for the MineRL Competition
Viaarxiv icon

Towards robust and domain agnostic reinforcement learning competitions

Jun 07, 2021
William Hebgen Guss, Stephanie Milani, Nicholay Topin, Brandon Houghton, Sharada Mohanty, Andrew Melnik, Augustin Harter, Benoit Buschmaas, Bjarne Jaster, Christoph Berganski, Dennis Heitkamp, Marko Henning, Helge Ritter, Chengjie Wu, Xiaotian Hao, Yiming Lu, Hangyu Mao, Yihuan Mao, Chao Wang, Michal Opanowicz, Anssi Kanervisto, Yanick Schraner, Christian Scheller, Xiren Zhou, Lu Liu, Daichi Nishio, Toi Tsuneda, Karolis Ramanauskas, Gabija Juceviciute

Figure 1 for Towards robust and domain agnostic reinforcement learning competitions
Figure 2 for Towards robust and domain agnostic reinforcement learning competitions
Figure 3 for Towards robust and domain agnostic reinforcement learning competitions
Figure 4 for Towards robust and domain agnostic reinforcement learning competitions
Viaarxiv icon

Dynamic Knapsack Optimization Towards Efficient Multi-Channel Sequential Advertising

Jun 29, 2020
Xiaotian Hao, Zhaoqing Peng, Yi Ma, Guan Wang, Junqi Jin, Jianye Hao, Shan Chen, Rongquan Bai, Mingzhou Xie, Miao Xu, Zhenzhe Zheng, Chuan Yu, Han Li, Jian Xu, Kun Gai

Figure 1 for Dynamic Knapsack Optimization Towards Efficient Multi-Channel Sequential Advertising
Figure 2 for Dynamic Knapsack Optimization Towards Efficient Multi-Channel Sequential Advertising
Figure 3 for Dynamic Knapsack Optimization Towards Efficient Multi-Channel Sequential Advertising
Figure 4 for Dynamic Knapsack Optimization Towards Efficient Multi-Channel Sequential Advertising
Viaarxiv icon

Learning to Accelerate Heuristic Searching for Large-Scale Maximum Weighted b-Matching Problems in Online Advertising

May 12, 2020
Xiaotian Hao, Junqi Jin, Jianye Hao, Jin Li, Weixun Wang, Yi Ma, Zhenzhe Zheng, Han Li, Jian Xu, Kun Gai

Figure 1 for Learning to Accelerate Heuristic Searching for Large-Scale Maximum Weighted b-Matching Problems in Online Advertising
Figure 2 for Learning to Accelerate Heuristic Searching for Large-Scale Maximum Weighted b-Matching Problems in Online Advertising
Figure 3 for Learning to Accelerate Heuristic Searching for Large-Scale Maximum Weighted b-Matching Problems in Online Advertising
Figure 4 for Learning to Accelerate Heuristic Searching for Large-Scale Maximum Weighted b-Matching Problems in Online Advertising
Viaarxiv icon

From Few to More: Large-scale Dynamic Multiagent Curriculum Learning

Sep 06, 2019
Weixun Wang, Tianpei Yang, Yong Liu, Jianye Hao, Xiaotian Hao, Yujing Hu, Yingfeng Chen, Changjie Fan, Yang Gao

Figure 1 for From Few to More: Large-scale Dynamic Multiagent Curriculum Learning
Figure 2 for From Few to More: Large-scale Dynamic Multiagent Curriculum Learning
Figure 3 for From Few to More: Large-scale Dynamic Multiagent Curriculum Learning
Figure 4 for From Few to More: Large-scale Dynamic Multiagent Curriculum Learning
Viaarxiv icon

Action Semantics Network: Considering the Effects of Actions in Multiagent Systems

Jul 26, 2019
Weixun Wang, Tianpei Yang Yong Liu, Jianye Hao, Xiaotian Hao, Yujing Hu, Yingfeng Chen, Changjie Fan, Yang Gao

Figure 1 for Action Semantics Network: Considering the Effects of Actions in Multiagent Systems
Figure 2 for Action Semantics Network: Considering the Effects of Actions in Multiagent Systems
Figure 3 for Action Semantics Network: Considering the Effects of Actions in Multiagent Systems
Figure 4 for Action Semantics Network: Considering the Effects of Actions in Multiagent Systems
Viaarxiv icon