Neuro-Symbolic Architecture for Experiential Learning in Discrete and Functional Environments

Author:

Kolonin Anton

Publisher

Springer International Publishing

Reference21 articles.

1. Tsamoura, E., Michael, L.: Neural-Symbolic Integration: A Compositional Perspective (2020). arXiv:2010.11926 [cs.AI]. https://arxiv.org/abs/2010.11926

2. Garcez, A., et al.: Neural-Symbolic Computing: An Effective Methodology for Principled Integration of Machine Learning and Reasoning (2019). arXiv:1905.06088 [cs.AI]

3. Silver, D., et al.: Reward is Enough. Artificial Intelligence, vol. 299 (October 2021). https://doi.org/10.1016/j.artint.2021.103535

4. Francois-Lavet, V., et al.: An Introduction to Deep Reinforcement Learning (2018). arXiv:1811.12560 [cs.LG]. https://arxiv.org/abs/1811.12560

5. Moreira, I., et al.: Deep Reinforcement Learning with Interactive Feedback in a Human-Robot Environment (2020). arXiv:2007.03363 [cs.AI]. https://arxiv.org/abs/2007.03363

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