Behavior Cloned Transformers are Neurosymbolic Reasoners

Ruoyao Wang, Peter Jansen, Marc Alexandre Côté, Prithviraj Ammanabrolu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this work, we explore techniques for augmenting interactive AI agents with information from symbolic modules, much like humans use tools like calculators and GPS systems to assist with arithmetic and navigation. We test our agent's abilities in text games-challenging benchmarks for evaluating the multi-step reasoning abilities of game agents in grounded, language-based environments. Our experimental study indicates that injecting the actions from these symbolic modules into the action space of a behavior cloned transformer agent increases performance on four text game benchmarks that test arithmetic, navigation, sorting, and common sense reasoning by an average of 22%, allowing an agent to reach the highest possible performance on unseen games. This action injection technique is easily extended to new agents, environments, and symbolic modules.

Original languageEnglish (US)
Title of host publicationEACL 2023 - 17th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference
PublisherAssociation for Computational Linguistics (ACL)
Pages2769-2780
Number of pages12
ISBN (Electronic)9781959429449
StatePublished - 2023
Event17th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2023 - Dubrovnik, Croatia
Duration: May 2 2023May 4 2023

Publication series

NameEACL 2023 - 17th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference

Conference

Conference17th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2023
Country/TerritoryCroatia
CityDubrovnik
Period5/2/235/4/23

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Software
  • Linguistics and Language

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