1. Adjodah, D., Klinger, T., & Joseph, J. (2018). Symbolic relation networks for reinforcement learning. In NeurIPS workshop on representation learning.
2. Agnew, W., & Domingos, P. (2018). Unsupervised object-level deep reinforcement learning. In NeurIPS workshop on deep RL.
3. Akrour, R., Tateo, D., & Peters, J. (2019). Towards reinforcement learning of human readable policies. In Workshop on deep continuous-discrete machine learning.
4. Aksaray, D., Jones, A., Kong, Z., et al. (2016). Q-Learning for robust satisfaction of signal temporal logic specifications. In CDC.
5. Alharin, A., Doan, T. N., & Sartipi, M. (2020). Reinforcement learning interpretation methods: A survey. IEEE Access, 8, 171058–171077.