all AI news
Asking for Knowledge: Training RL Agents to Query External Knowledge Using Language. (arXiv:2205.06111v2 [cs.AI] UPDATED)
July 5, 2022, 1:12 a.m. | Iou-Jen Liu, Xingdi Yuan, Marc-Alexandre Côté, Pierre-Yves Oudeyer, Alexander G. Schwing
cs.CL updates on arXiv.org arxiv.org
To solve difficult tasks, humans ask questions to acquire knowledge from
external sources. In contrast, classical reinforcement learning agents lack
such an ability and often resort to exploratory behavior. This is exacerbated
as few present-day environments support querying for knowledge. In order to
study how agents can be taught to query external knowledge via language, we
first introduce two new environments: the grid-world-based Q-BabyAI and the
text-based Q-TextWorld. In addition to physical interactions, an agent can
query an external knowledge …
More from arxiv.org / cs.CL updates on arXiv.org
Jobs in AI, ML, Big Data
Artificial Intelligence – Bioinformatic Expert
@ University of Texas Medical Branch | Galveston, TX
Lead Developer (AI)
@ Cere Network | San Francisco, US
Research Engineer
@ Allora Labs | Remote
Ecosystem Manager
@ Allora Labs | Remote
Founding AI Engineer, Agents
@ Occam AI | New York
AI Engineer Intern, Agents
@ Occam AI | US