About cookies on this site Our websites require some cookies to function properly (required). In addition, other cookies may be used with your consent to analyze site usage, improve the user experience and for advertising. For more information, please review your options. By visiting our website, you agree to our processing of information as described in IBM’sprivacy statement. To provide a smooth navigation, your cookie preferences will be shared across the IBM web domains listed here.
Publication
NAACL 2022
Workshop paper
Challenges in Explainability and Knowledge Extraction
Abstract
Since text-based games are one of the most challenging problems and require to have an understanding of language and decision-making in a complex environment, there are many studies about applying deep reinforcement learning methods. However, these deep models are often black-box which means the human operator cannot understand the trained rules. And the models use external knowledge such as common-sense knowledge from well-designed data. In this paper, we explain some challenges in text-based games.