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Text Worlds are virtual environments for embodied agents that, unlike 2D or3D environments, are rendered exclusively using textual descriptions. Theseenvironments offer an alternative to higher-fidelity 3D environments due totheir low barrier to entry, providing the ability to study semantics,compositional inference, and other high-level tasks with rich high-level actionspaces while controlling for perceptual input. This systematic survey outlinesrecent developments in tooling, environments, and agent modeling for TextWorlds, while examining recent trends in knowledge graphs, common sensereasoning, transfer learning of Text World performance to higher-fidelityenvironments, as well as near-term development targets that, once achieved,make Text Worlds an attractive general research paradigm for natural languageprocessing.

A Systematic Survey of Text Worlds as Embodied Natural Language Environments