Papers › ALFWorld: Aligning Text and Embodied Environments for Interactive Learning

ALFWorld: Aligning Text and Embodied Environments for Interactive Learning

8 Oct 2020arXiv:2010.03768archive 2025-07-28

Mohit Shridhar, Xingdi Yuan, Marc-Alexandre Côté, Yonatan Bisk, Adam Trischler, Matthew Hausknecht

Given a simple request like Put a washed apple in the kitchen fridge, humans can reason in purely abstract terms by imagining action sequences and scoring their likelihood of success, prototypicality, and efficiency, all without moving a muscle. Once we see the kitchen in question, we can update our abstract plans to fit the scene. Embodied agents require the same abilities, but existing work does not yet provide the infrastructure necessary for both reasoning abstractly and executing concretely. We address this limitation by introducing ALFWorld, a simulator that enables agents to learn abstract, text based policies in TextWorld (C\^ot\'e et al., 2018) and then execute goals from the ALFRED benchmark (Shridhar et al., 2020) in a rich visual environment. ALFWorld enables the creation of a new BUTLER agent whose abstract knowledge, learned in TextWorld, corresponds directly to concrete, visually grounded actions. In turn, as we demonstrate empirically, this fosters better agent generalization than training only in the visually grounded environment. BUTLER's simple, modular design factors the problem to allow researchers to focus on models for improving every piece of the pipeline (language understanding, planning, navigation, and visual scene understanding).

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BoxFeaturesFC alfworld/alfworld/alfworld/agents/modules/model.py official repository ran MIT (permissive) · 42db735ed71ca183 · report
CQAttention alfworld/alfworld/alfworld/agents/modules/model.py official repository ran MIT (permissive) · 676a78e4b2463f42 · report
DecoderBlock alfworld/alfworld/alfworld/agents/modules/model.py official repository ran MIT (permissive) · eaa6cae4d498c74a · report
DepthwiseSeparableConv alfworld/alfworld/alfworld/agents/modules/model.py official repository ran fingerprinted MIT (permissive) · 189fed4e56b7291e · report
NoisyLinear alfworld/alfworld/alfworld/agents/modules/model.py official repository ran MIT (permissive) · a81a851773abf04b · report
PointerSoftmax alfworld/alfworld/alfworld/agents/modules/model.py official repository ran MIT (permissive) · b12dcd1f191784bb · report
PosEncoder alfworld/alfworld/alfworld/agents/modules/model.py official repository ran · our draft was wrong fingerprinted MIT (permissive) · 6dda823ca190d07a · report
ScaledDotProductAttention alfworld/alfworld/alfworld/agents/modules/model.py official repository ran MIT (permissive) · 540b60f3c35ddb5c · report
compute_mask alfworld/alfworld/alfworld/agents/modules/model.py official repository ran · our draft was wrong fingerprinted MIT (permissive) · 91eb0af694a5d554 · report
get_timing_signal alfworld/alfworld/alfworld/agents/modules/model.py official repository ran · honoured contract fingerprinted MIT (permissive) · 91d294d891ea41db · report
masked_softmax alfworld/alfworld/alfworld/agents/modules/model.py official repository ran · our draft was wrong fingerprinted MIT (permissive) · e5002de1b930b693 · report
EncoderBlock alfworld/alfworld/alfworld/agents/modules/model.py official repository unverified MIT (permissive) · 72bcf63ba171e486 · report
Policy alfworld/alfworld/alfworld/agents/modules/model.py official repository unverified MIT (permissive) · 2ee19fbc662f9365 · report
SelfAttention alfworld/alfworld/alfworld/agents/modules/model.py official repository unverified MIT (permissive) · 4b8de7bded2e4118 · report

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Natural Language Visual GroundingScene Understanding

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ALFWorld

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