Question asking as program generation

Rothe, A., Lake, B. M., & Gureckis, T. M. (2017). Question asking as program generation. Advances in Neural Information Processing Systems, 1046–1055.


Abstract

A hallmark of human intelligence is the ability to ask rich, creative, and revealing questions. Here we introduce a cognitive model capable of constructing humanlike questions. Our approach treats questions as formal programs that, when executed on the state of the world, output an answer. The model specifies a probability distribution over a complex, compositional space of programs, favoring concise programs that help the agent learn in the current context. We evaluate our approach by modeling the types of open-ended questions generated by humans who were attempting to learn about an ambiguous situation in a game. We find that our model predicts what questions people will ask, and can creatively produce novel questions that were not present in the training set. In addition, we compare a number of model variants, finding that both question informativeness and complexity are important for producing human-like questions.


Highlighted Figures


Bibtex entry:

@inproceedings{rothe2017question,
	abstract = {A hallmark of human intelligence is the ability to ask rich, creative, and revealing questions. Here we introduce a cognitive model capable of constructing humanlike questions. Our approach treats questions as formal programs that, when executed on the state of the world, output an answer. The model specifies a probability distribution over a complex, compositional space of programs, favoring concise programs that help the agent learn in the current context. We evaluate our approach by modeling the types of open-ended questions generated by humans who were attempting to learn about an ambiguous situation in a game. We find that our model predicts what questions people will ask, and can creatively produce novel questions that were not present in the training set. In addition, we compare a number of model variants, finding that both question informativeness and complexity are important for producing human-like questions.},
	author = {Rothe, A. and Lake, B.M. and Gureckis, T.M.},
	booktitle = {Advances in Neural Information Processing Systems},
	journal = {arXiv preprint arXiv:1711.06351},
	pages = {1046-1055},
	title = {Question asking as program generation},
	year = {2017}}


QR Code:


Download SVG