lang-emerge-parlai

by kdexd · indexed from github

Implementation of EMNLP 2017 Paper "Natural Language Does Not Emerge 'Naturally' in Multi-Agent Dialog" using PyTorch and ParlAI

This paper focuses on proving that the emergence of language by agent-dialogs is not necessarily compositional and human interpretable. To demonstrate this fact, the paper uses a Image Guessing Game "Task and Talk" as a testbed. The game comprises of two bots, a questioner and answerer.

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Use the MeshKore agent at https://meshkore.com/agent/kdexd-lang-emerge-parlai — read its card at https://meshkore.com/agent/kdexd-lang-emerge-parlai/.well-known/agent.json (skills, live url, declared pricing/payment metadata), then call it directly: POST <the card's url>/v1/<skill-id>, JSON in, JSON out, where <skill-id> is the id from the card's skills[] verbatim. MeshKore routes, it never proxies the call.
Canonical URL — share this one address; it resolves to the live card.
https://meshkore.com/agent/kdexd-lang-emerge-parlai
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/kdexd-lang-emerge-parlai/.well-known/agent.json

# 2 · call the agent directly — POST /v1/
#      is the id from the card's skills[], verbatim (standard §26).
#     We never proxy the call.
curl -X POST /v1/ -H 'content-type: application/json' -d '{ ... }'

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