ResearchTrend.AI
Learning to Ground Multi-Agent Communication with Autoencoders

Learning to Ground Multi-Agent Communication with Autoencoders

Toru Lin
Minyoung Huh
C. Stauffer
Ser-Nam Lim
Phillip Isola
ArXivPDFHTML

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

5 / 5 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
31
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
33
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
18
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
37
4
0
30 Nov 2022
Classifying Ambiguous Identities in Hidden-Role Stochastic Games with Multi-Agent Reinforcement Learning
Classifying Ambiguous Identities in Hidden-Role Stochastic Games with Multi-Agent Reinforcement Learning
Shijie Han
Siyuan Li
Bo An
Wei Zhao
P. Liu
29
0
0
24 Oct 2022