Neuro Symbolic AI for Sequential Decision Making

Author:

Shakarian Paulo,Baral Chitta,Simari Gerardo I.,Xi Bowen,Pokala Lahari

Publisher

Springer Nature Switzerland

Reference14 articles.

1. Brockman, G., Cheung, V., Pettersson, L., Schneider, J., Schulman, J., Tang, J., Zaremba, W.: Openai gym. arXiv preprint arXiv:1606.01540 (2016)

2. Corso, A., Moss, R., Koren, M., Lee, R., Kochenderfer, M.: A survey of algorithms for black-box safety validation of cyber-physical systems. J. Artif. Int. Res. 72, 377–428 (2022)

3. Hekmatnejad, M., Hoxha, B., Deshmukh, J.V., Yang, Y., Fainekos, G.: Formalizing and evaluating requirements of perception systems for automated vehicles using spatio-temporal perception logic (2022). https://doi.org/10.48550/ARXIV.2206.14372. https://arxiv.org/abs/2206.14372

4. Kamienny, P.A., d’Ascoli, S., Lample, G., Charton, F.: End-to-end symbolic regression with transformers. In: Oh, A.H., Agarwal, A., Belgrave, D., Cho, K. (eds.) Advances in Neural Information Processing Systems (2022)

5. Kimura, D., Chaudhury, S., Wachi, A., Kohita, R., Munawar, A., Tatsubori, M., Gray, A.: Reinforcement learning with external knowledge by using logical neural networks. CoRR abs/2103.02363 (2021). https://arxiv.org/abs/2103.02363

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