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text-based games

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Text-based games to evaluate the Reinforcement Learning Agents

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/Exploration-Lab/IFG-Pretrained-LM

공식 코드

Pre-trained Language Models as Prior Knowledge for Playing Text-based Games

https://github.com/IBM/commonsense-rl

공식 코드

Text-based RL Agents with Commonsense Knowledge: New Challenges, Environments and Baselines

https://github.com/IBM/context-relevant-pruning-textrl

공식 코드

Bootstrapped Q-learning with Context Relevant Observation Pruning to Generalize in Text-based Games

https://github.com/MikulasZelinka/pyfiction

공식 코드

Using reinforcement learning to learn how to play text-based games

https://github.com/MikulasZelinka/textworld_kg_dataset

공식 코드

Building Dynamic Knowledge Graphs from Text-based Games

https://github.com/YunqiuXu/SHA-KG

공식 코드

Deep Reinforcement Learning with Stacked Hierarchical Attention for Text-based Games

https://github.com/benjamintowle/pasa

공식 코드

Learn What Is Possible, Then Choose What Is Best: Disentangling One-To-Many Relations in Language Through Text-based Games

https://github.com/cognitiveailab/bytesized32

공식 코드

ByteSized32: A Corpus and Challenge Task for Generating Task-Specific World Models Expressed as Text Games

https://github.com/cognitiveailab/textworldexpress

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TextWorldExpress: Simulating Text Games at One Million Steps Per Second

https://github.com/exploration-lab/scriptworld

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ScriptWorld: Text Based Environment For Learning Procedural Knowledge

https://github.com/fhudi/textgames

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TextGames: Learning to Self-Play Text-Based Puzzle Games via Language Model Reasoning

https://github.com/hyintell/llmsymbolic

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Large Language Models Are Neurosymbolic Reasoners

https://github.com/ibm/diffg-rl

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DiffG-RL: Leveraging Difference between State and Common Sense

https://github.com/ibm/loa

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LOA: Logical Optimal Actions for Text-based Interaction Games

https://github.com/ibm/starling-agent

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STARLING: Self-supervised Training of Text-based Reinforcement Learning Agent with Large Language Models

https://github.com/jnanliu/situatedthinker

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SituatedThinker: Grounding LLM Reasoning with Real-World through Situated Thinking

https://github.com/kinjalbasu/explorer

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EXPLORER: Exploration-guided Reasoning for Textual Reinforcement Learning

https://github.com/ktr0921/tac

공식 코드

A Minimal Approach for Natural Language Action Space in Text-based Games

https://github.com/leonguertler/textarena

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TextArena

https://github.com/mathieutuli/ltl-gata

공식 코드

Learning to Follow Instructions in Text-Based Games

https://github.com/princeton-nlp/calm-textgame

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Keep CALM and Explore: Language Models for Action Generation in Text-based Games

https://github.com/pull-ups/PANDA

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Persona Dynamics: Unveiling the Impact of Personality Traits on Agents in Text-Based Games

https://github.com/rajammanabrolu/Q-BERT

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How To Avoid Being Eaten By a Grue: Exploration Strategies for Text-Adventure Agents

https://github.com/weichenli1223/text-based-adventure-games-using-sac

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Learning to Play Text-based Adventure Games with Maximum Entropy Reinforcement Learning

https://github.com/xingdi-eric-yuan/GATA-public

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Learning Dynamic Belief Graphs to Generalize on Text-Based Games

https://github.com/xingdi-eric-yuan/TextWorld-Coin-Collector

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Counting to Explore and Generalize in Text-based Games

https://github.com/yukw777/temporal-discrete-graph-updater

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Constructing Temporal Dynamic Knowledge Graphs from Interactive Text-based Games

https://github.com/yunqiuxu/h-kga

공식 코드

Generalization in Text-based Games via Hierarchical Reinforcement Learning

https://github.com/yunqiuxu/qwa

공식 코드

Perceiving the World: Question-guided Reinforcement Learning for Text-based Games

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.