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CHALET: Cornell House Agent Learning Environment

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arxiv 1801.07357 v2 pith:HIE5QQ56 submitted 2018-01-23 cs.AI

Claudia Yan , Dipendra Misra , Andrew Bennnett , Aaron Walsman , Yonatan Bisk , Yoav Artzi This is my paper · ORCID
classification cs.AI
keywords chalethouseenvironmentcreateincludingobjectsactionsactivities
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We present CHALET, a 3D house simulator with support for navigation and manipulation. CHALET includes 58 rooms and 10 house configuration, and allows to easily create new house and room layouts. CHALET supports a range of common household activities, including moving objects, toggling appliances, and placing objects inside closeable containers. The environment and actions available are designed to create a challenging domain to train and evaluate autonomous agents, including for tasks that combine language, vision, and planning in a dynamic environment.

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Cited by 1 Pith paper

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  1. Language Tasks and Language Games: On Methodology in Current Natural Language Processing Research

    cs.CL 2019-08 accept novelty 6.0 of 10

    A methodology paper that formalizes tasks, worlds, and games in NLP and argues that progress claims require explicit assumptions about decomposable language capabilities.

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