ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2209.07225
  4. Cited By
MIXRTs: Toward Interpretable Multi-Agent Reinforcement Learning via Mixing Recurrent Soft Decision Trees

MIXRTs: Toward Interpretable Multi-Agent Reinforcement Learning via Mixing Recurrent Soft Decision Trees

15 September 2022
Zichuan Liu
Zichuan Liu
Zhi Wang
Yuanyang Zhu
Chunlin Chen
ArXivPDFHTML

Papers citing "MIXRTs: Toward Interpretable Multi-Agent Reinforcement Learning via Mixing Recurrent Soft Decision Trees"

4 / 4 papers shown
Title
Higher Replay Ratio Empowers Sample-Efficient Multi-Agent Reinforcement
  Learning
Higher Replay Ratio Empowers Sample-Efficient Multi-Agent Reinforcement Learning
Linjie Xu
Zichuan Liu
Alexander Dockhorn
Diego Perez-Liebana
Jinyu Wang
Lei Song
Jiang Bian
38
2
0
15 Apr 2024
Multi-Agent Reinforcement Learning: Methods, Applications, Visionary
  Prospects, and Challenges
Multi-Agent Reinforcement Learning: Methods, Applications, Visionary Prospects, and Challenges
Ziyuan Zhou
Guanjun Liu
Ying-Si Tang
28
14
0
17 May 2023
N$\text{A}^\text{2}$Q: Neural Attention Additive Model for Interpretable
  Multi-Agent Q-Learning
NA2\text{A}^\text{2}A2Q: Neural Attention Additive Model for Interpretable Multi-Agent Q-Learning
Zichuan Liu
Yuanyang Zhu
Chunlin Chen
27
10
0
26 Apr 2023
Deep Reinforcement Learning for Autonomous Driving: A Survey
Deep Reinforcement Learning for Autonomous Driving: A Survey
B. R. Kiran
Ibrahim Sobh
V. Talpaert
Patrick Mannion
A. A. Sallab
S. Yogamani
P. Pérez
143
1,599
0
02 Feb 2020
1