Simulating Action Dynamics with Neural Process Networks

  title={Simulating Action Dynamics with Neural Process Networks},
  author={Antoine Bosselut and Omer Levy and Ari Holtzman and Corin Ennis and Dieter Fox and Yejin Choi},
Understanding procedural language requires anticipating the causal effects of actions, even when they are not explicitly stated. In this work, we introduce Neural Process Networks to understand procedural text through (neural) simulation of action dynamics. Our model complements existing memory architectures with dynamic entity tracking by explicitly modeling actions as state transformers. The model updates the states of the entities by executing learned action operators. Empirical results… CONTINUE READING

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