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arXiv · 1806.11525

Counting to Explore and Generalize in Text-based Games

Xingdi Yuan·Marc-Alexandre Côté·Alessandro Sordoni·Romain Laroche·Remi Tachet des Combes·Matthew Hausknecht·Adam Trischler
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Abstract

We propose a recurrent RL agent with an episodic exploration mechanism that helps discovering good policies in text-based game environments. We show promising results on a set of generated text-based games of varying difficulty where the goal is to collect a coin located at the end of a chain of rooms. In contrast to previous text-based RL approaches, we observe that our agent learns policies that generalize to unseen games of greater difficulty.

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Xingdi Yuan, Marc-Alexandre Côté, Alessandro Sordoni, Romain Laroche, Remi Tachet des Combes, Matthew Hausknecht, Adam Trischler. 2018-06-29. Counting to Explore and Generalize in Text-based Games. https://arxiv.org/abs/1806.11525

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