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Language Understanding for Text-based Games Using Deep Reinforcement Learning

arXiv 1506.08941 ↗First posted 30 Jun 2015cs.CL cs.AIcited by 70

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Abstract (arXiv)

In this paper, we consider the task of learning control policies for text-based games. In these games, all interactions in the virtual world are through text and the underlying state is not observed. The resulting language barrier makes such environments challenging for automatic game players. We employ a deep reinforcement learning framework to jointly learn state representations and action policies using game rewards as feedback. This framework enables us to map text descriptions into vector representations that capture the semantics of the game states. We evaluate our approach on two game worlds, comparing against baselines using bag-of-words and bag-of-bigrams for state representations. Our algorithm outperforms the baselines on both worlds demonstrating the importance of learning expressive representations.

Key facts. Cited by 70 papers in the map (data through 7 Oct 2026). First posted on arXiv 30 Jun 2015.

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Citing papers per year: 2019: 1; 2020: 0; 2021: 20; 2022: 10; 2023: 16; 2024: 6; 2025: 11; 2026: 6.

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  2. 2025Group-in-Group Policy Optimization for LLM Agent Trainingcited by 442
  3. 2022Pre-Trained Language Models for Interactive Decision-Makingcited by 220
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  6. 2023Guiding Large Language Models via Directional Stimulus Promptingcited by 94
  7. 2023LMRL Gym: Benchmarks for Multi-Turn Reinforcement Learning with Language Modelscited by 84
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  10. 2026Hierarchy-of-Groups Policy Optimization for Long-Horizon Agentic Taskscited by 37
  11. 2021Efficient (Soft) Q-Learning for Text Generation with Limited Good Datacited by 35
  12. 2023Inference-Time Policy Adapters (IPA): Tailoring Extreme-Scale LMs without Fine-tuningcited by 33
38 more
  1. 2021Survey on reinforcement learning for language processingcited by 31
  2. 2021Learning Knowledge Graph-based World Models of Textual Environmentscited by 31
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  4. 2023LLF-Bench: Benchmark for Interactive Learning from Language Feedbackcited by 30
  5. 2023Augmenting Autotelic Agents with Large Language Modelscited by 29
  6. 2022Multi-Stage Episodic Control for Strategic Exploration in Text Gamescited by 22
  7. 2025Monte Carlo Planning with Large Language Model for Text-Based Game Agentscited by 22
  8. 2026AgentOCR: Reimagining Agent History via Optical Self-Compressioncited by 22
  9. 2021Reading and Acting while Blindfolded: The Need for Semantics in Text Game Agentscited by 20
  10. 2025debug-gym: A Text-Based Environment for Interactive Debuggingcited by 19
  11. 2021A Systematic Survey of Text Worlds as Embodied Natural Language Environmentscited by 17
  12. 2021Towards Socially Intelligent Agents with Mental State Transition and Human Utilitycited by 14
  13. 2021Training Value-Aligned Reinforcement Learning Agents Using a Normative Priorcited by 14
  14. 2021A Survey of Text Games for Reinforcement Learning informed by Natural Languagecited by 14
  15. 2025Reinforcement Learning for Machine Learning Engineering Agentscited by 13
  16. 2022TextWorldExpress: Simulating Text Games at One Million Steps Per Secondcited by 12
  17. 2022Learning to Follow Instructions in Text-Based Gamescited by 12
  18. 2024Babysit A Language Model From Scratch: Interactive Language Learning by Trials and Demonstrationscited by 12
  19. 2021Generalization in Text-based Games via Hierarchical Reinforcement Learningcited by 11
  20. 2025STEP: Success-Rate-Aware Trajectory-Efficient Policy Optimizationcited by 11
  21. 2021Reinforcement Learning with External Knowledge by using Logical Neural Networkscited by 10
  22. 2022Perceiving the World: Question-guided Reinforcement Learning for Text-based Gamescited by 10
  23. 2022Reinforcement Learning and Bandits for Speech and Language Processing: Tutorial, Review and Outlookcited by 10
  24. 2022Improving Policy Learning via Language Dynamics Distillationcited by 9
  25. 2023Predictive Chemistry Augmented with Text Retrievalcited by 9
  26. 2024A Survey On Enhancing Reinforcement Learning in Complex Environments: Insights from Human and LLM Feedbackcited by 9
  27. 2025AuthorMist: Evading AI Text Detectors with Reinforcement Learningcited by 9
  28. 2025TALES: Text Adventure Learning Environment Suitecited by 9
  29. 2021Case-based Reasoning for Better Generalization in Textual Reinforcement Learningcited by 8
  30. 2019Action Assembly: Sparse Imitation Learning for Text Based Games with Combinatorial Action Spacescited by 7
  31. 2026Group-Graph Policy Optimization for Long-Horizon Agentic Reinforcement Learningcited by 7
  32. 2021LOA: Logical Optimal Actions for Text-based Interaction Gamescited by 6
  33. 2023Thespian: Multi-Character Text Role-Playing Game Agentscited by 6
  34. 2021Designing an Automatic Agent for Repeated Language based Persuasion Gamescited by 5
  35. 2023Ambient Adventures: Teaching ChatGPT on Developing Complex Storiescited by 5
  36. 2023An Invitation to Deep Reinforcement Learningcited by 5
  37. 2026SIRI: Self-Internalizing Reinforcement Learning with Intrinsic Skills for LLM Agent Trainingcited by 5
  38. 2021Eye of the Beholder: Improved Relation Generalization for Text-based Reinforcement Learning Agentscited by 4

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