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EMNLP 2017 Code for "Natural Language Does Not Emerge 'Naturally' in Multi-Agent Dialog"
PyTorch code for Learning Cooperative Visual Dialog Agents using Deep Reinforcement Learning
On the pitfalls of measuring emergent communication
Emergent Translation in Multi-Agent Communication PyTorch implementation of the models described in the paper Emergent Translation in Multi-Agent Communication.
Source code for Emergent Communication in a Multi-Modal, Multi-Step Referential Game.
The main features of nyu-dl/multimodalgame are: Multi-agent Communication.
Projects with overlapping indexed features include: batra-mlp-lab/lang-emerge — [EMNLP 2017] Code for "Natural Language Does Not Emerge 'Naturally' in Multi-Agent Dialog". batra-mlp-lab/visdial-rl — PyTorch code for Learning Cooperative Visual Dialog Agents using Deep Reinforcement Learning. facebookresearch/measuring-emergent-comm — On the pitfalls of measuring emergent communication. facebookresearch/translagent — Emergent Translation in Multi-Agent Communication PyTorch implementation of the models described in the paper Emergent… kdexd/lang-emerge-parlai — Implementation of EMNLP 2017 Paper "Natural Language Does Not Emerge 'Naturally' in Multi-Agent Dialog" using PyTorch…