Fork me on GitHub

Trending arXiv

Note: this version is tailored to @Smerity - though you can run your own! Trending arXiv may eventually be extended to multiple users ...


Rationalization: A Neural Machine Translation Approach to Generating Natural Language Explanations

Brent Harrison, Upol Ehsan, Mark O. Riedl

We introduce AI rationalization, an approach for generating explanations of autonomous system behavior as if a human had done the behavior. We describe a rationalization technique that uses neural machine translation to translate internal state-action representations of the autonomous agent into natural language. We evaluate our technique in the Frogger game environment. The natural language is collected from human players thinking out loud as they play the game. We motivate the use of rationalization as an approach to explanation generation, show the results of experiments on the accuracy of our rationalization technique, and describe future research agenda.

Captured tweets and retweets: 2