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. 2110.15349
  4. Cited By
Learning to Ground Multi-Agent Communication with Autoencoders

Learning to Ground Multi-Agent Communication with Autoencoders

28 October 2021
Toru Lin
Minyoung Huh
C. Stauffer
Ser-Nam Lim
Phillip Isola
    AI4CE
ArXivPDFHTML

Papers citing "Learning to Ground Multi-Agent Communication with Autoencoders"

4 / 4 papers shown
Title
A Review of the Applications of Deep Learning-Based Emergent
  Communication
A Review of the Applications of Deep Learning-Based Emergent Communication
Brendon Boldt
David R. Mortensen
VLM
21
6
0
03 Jul 2024
CoMIX: A Multi-agent Reinforcement Learning Training Architecture for
  Efficient Decentralized Coordination and Independent Decision-Making
CoMIX: A Multi-agent Reinforcement Learning Training Architecture for Efficient Decentralized Coordination and Independent Decision-Making
Giovanni Minelli
Mirco Musolesi
13
0
0
21 Aug 2023
Cooperative Multi-Agent Learning for Navigation via Structured State
  Abstraction
Cooperative Multi-Agent Learning for Navigation via Structured State Abstraction
Mohamed K. Abdel-Aziz
Mohammed S. Elbamby
S. Samarakoon
M. Bennis
8
4
0
20 Jun 2023
Towards True Lossless Sparse Communication in Multi-Agent Systems
Towards True Lossless Sparse Communication in Multi-Agent Systems
Seth Karten
Mycal Tucker
Siva Kailas
Katia P. Sycara
16
4
0
30 Nov 2022
1