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          REFERENCES
          Andrychowicz, M., Denil, M., Gomez, S., Hoffman, M. W., Pfau, D., Schaul, T., et al.
             (2016). Learning to learn by gradient descent by gradient descent. In Advances in neural
             information processing systems (pp. 3981–3989).
          Aswani, A., Gonzalez, H., Sastry, S. S., & Tomlin, C. J. (2013). Provably safe and robust
             learning-based model predictive control. Automatica, 49(5), 1216–1226.
          Azim, M. T., Neamtiu, I., & Marvel, L. M. (2014). Towards self-healing smartphone
             software via automated patching. In: In Proceedings of the 29th ACM/IEEE international
             conference on automated software engineering (pp. 623–628) ACM.
          Berman, S., Hala ´sz, A. M., Hsieh, M. A., & Kumar, V. (2009). Optimized stochastic policies
             for task allocation in swarms of robots. IEEE Transactions on Robotics, 25, 927–937.
          Berman, S., Lindsey, Q., Sakar, M. S., Kumar, V., & Pratt, S. (2011). Experimental study and
             modeling of group retrieval in ants as an approach to collective transport in swarm
             robotic systems. Proceedings of the IEEE, 99, 1470–1481.
          Bojarski, M.; Del Testa, D.; Dworakowski, D.; Firner, B.; Flepp, B.; Goyal, P.; Jackel, L.D.;
             Monfort, M. Muller, U.; Zhang, J.; et al. End to end learning for self-driving cars. arXiv
             preprint arXiv:1604.07316, 2016.
          Boots, B., Siddiqi, S. M., & Gordon, G. J. (2011). Closing the learning-planning loop with
             predictive state representations. The International Journal of Robotics Research (IJRR), 30(7),
             954–966.
          Byravan, A., & Fox, D. (2017). SE3-nets: learning rigid body motion using deep neural
             networks. In: Proceedings of the IEEE international conference on robotics & automation (ICRA).
          Carlini, N., & Wagner, D. (2017). Adversarial examples are not easily detected: bypassing ten
             detection methods. In: In Proceedings of the 10th ACM workshop on artificial intelligence and
             security (pp. 3–14) ACM.
          CBS News. (2017). Digital doubles: bringing actors back to life. February 26, 2017 https://www.
             cbsnews.com/news/digital-doubles-bringing-actors-back-to-life/.
          Chu, B., Madhavan, V., Beijbom, O., Hoffman, J., & Darrell, T. (2016). Best practices for
             fine-tuning visual classifiers to new domains. In European conference on computer vision, (pp.
             435–442). Cham: Springer (pp. 435–442).
          De Gaspari, F., Jajodia, S., Mancini, L. V., & Panico, A. (2016). AHEAD: a new architecture
             for active defense. In Proceedings of the 2016 ACM workshop on automated decision making for
             active cyber defense (pp. 11–16). Vienna, Austria: ACM.
          Deng, J., Dong, W., Socher, R., Li, L., Li, K., & Fei-Fei, L. (2009). Imagenet: a large-scale
             hierarchical image database. In IEEE conference on computer vision and pattern recognition
             (pp. 248–255).
          Devin, C., Gupta, A., Darrell, T., Abbeel, P., & Levine, S. (2017). Learning modular neural
             network policies for multi-task and multi-robot transfer. In International conference on
             robotics and automation (ICRA).
          Fernando, B.; Habrard, A.; Sebban, M.; and Tuytelaars, T. Unsupervised visual domain
             adaptation using subspace alignment. In Computer vision (ICCV), 2013 IEEE interna-
             tional conference on, pp. 2960-2967. IEEE, 2013.
          Finn, C., Abbeel, P., & Levine, S. (2017). Model-agnostic meta-learning for fast adaptation
             of deep networks. In International conference on machine learning (ICML).
          Freedberg, S. J., Jr. (2016). Missile defense for tanks: Raytheon quick kill vs. Israeli trophy.
             Breakingdefense.com.
          Giridhar, P., Wang, S., Abdelzaher, T. F., Al Amin, T., & Kaplan, L. M. (2017). Social
             fusion: integrating twitter and instagram for event monitoring. In 2017 IEEE Interna-
             tional Conference on Autonomic Computing (ICAC) (pp. 1–10).
          Gong, B., Shi, Y., Sha, F., & Grauman, K. (2012). Geodesic flow kernel for unsupervised
             domain adaptation. In Computer vision and pattern recognition (CVPR), 2012 IEEE confer-
             ence on (pp. 2066–2073). IEEE.
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