Encoding formulas as deep networks: Reinforcement learning for zero-shot execution of LTL formulas
We demonstrate a reinforcement learning agent which uses a compositional recurrent neural network that takes as input an LTL formula and determines satisfying actions. The input LTL formulas have never been seen before, yet the network performs zero-shot generalization to satisfy them. This is a nov...
| Main Authors: | , , |
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| Format: | Article |
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Center for Brains, Minds and Machines (CBMM), The Ninth International Conference on Learning Representations (ICLR)
2022
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| Online Access: | https://hdl.handle.net/1721.1/141355 |