Papers with multi-agent language learning
Multi-Agent Language Learning: Symbolic Mapping (2023.findings-acl)
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| Challenge: | Recent work has focused on the emergence of language in cooperative tasks where neural network agents learn a communication protocol from scratch to solve problems together. |
| Approach: | They propose a task transfer method and symbolic mapping architecture to help agents learn a compositional and symmetric language in dialog games. |
| Outcome: | The proposed method can help agents learn a compositional and symmetric language in complex settings like dialog games and the proposed architecture promotes vocabulary expansion. |