Fire burns, sword cuts: commonsense inductive bias for exploration in text-based games

Dongwon K. Ryu, Ehsan Shareghi, Meng Fang, Yunqiu Xu, Shirui Pan, Reza Haffari

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Abstract

Text-based games (TGs) are exciting testbeds for developing deep reinforcement learning techniques due to their partially observed environments and large action spaces. In these games, the agent learns to explore the environment via natural language interactions with the game simulator. A fundamental challenge in TGs is the efficient exploration of the large action space when the agent has not yet acquired enough knowledge about the environment. We propose CommExpl, an exploration technique that injects external commonsense knowledge, via a pretrained language model (LM), into the agent during training when the agent is the most uncertain about its next action. Our method exhibits improvement on the collected game scores during the training in four out of nine games from Jericho. Additionally, the produced trajectory of actions exhibit lower perplexity, when tested with a pretrained LM, indicating better closeness to human language.
Original languageEnglish
Title of host publicationACL 2022, The 60th Annual Meeting of the Association for Computational Linguistics
Subtitle of host publicationProceedings of the Conference, Vol. 2 (Short Papers)
EditorsDanilo Croce, Ryan Cotterell, Jordan Zhang
Place of PublicationStroudsburg PA USA
PublisherAssociation for Computational Linguistics (ACL)
Pages515–522
Number of pages8
ISBN (Electronic)9781955917223
Publication statusPublished - 2022
EventAnnual Meeting of the Association for Computational Linguistics 2022 - Dublin, Ireland
Duration: 22 May 202227 May 2022
Conference number: 60th
https://aclanthology.org/volumes/2022.acl-short/ (Proceedings - Short)
https://aclanthology.org/volumes/2022.acl-long/ (Proceedings - Long)
https://www.2022.aclweb.org/ (Website)

Conference

ConferenceAnnual Meeting of the Association for Computational Linguistics 2022
Abbreviated titleACL 2022
Country/TerritoryIreland
CityDublin
Period22/05/2227/05/22
Internet address

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