Publications

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Ognibene, D., and Baldassarre, G., Ecological Active Vision: Four Bio-Inspired Principles to Integrate Bottom-Up and Adaptive Top-Down Attention Tested With a Simple Camera-Arm Robot, Autonomous Mental Development, IEEE Transactions on, 2014.
Ognibene, D., Ecological Adaptive Perception from a Neuro-Robotic perspective: theory, architecture and experiments., University of Genoa, 2009.
Albore, A., Ramírez, M., and Geffner, H., Effective Heuristics and Belief Tracking for Planning with Incomplete Information, Proc. of Int. Conf. Automated Planning & Scheduling (ICAPS-11), Freiburg, Germany: 2011, pp. 2–9. Slides of the ICAPS presentation (210.16 KB) Paper ICAPS (192.95 KB)
Francès, G., and Geffner, H., Effective Planning with More Expressive Languages, Proc. 25th Int. Joint Conf. on Artificial Intelligence, 2016.
Neu, G., and Bartók, G., An Efficient Algorithm for Learning with Semi-Bandit Feedback, Proceedings of the 24th International Conference on Algorithmic Learning Theory (ALT), 2013, pp. 234-248.
Kocák, T. \vs, Neu, G., Valko, M., and Munos, R., Efficient learning by implicit exploration in bandit problems with side observations, Advances in Neural Information Processing Systems 27 (NIPS), 2014, pp. 613-621.
Jonsson, A., Efficient Pruning of Operators in Planning Domains, Lecture Notes in Artificial Intelligence: Current Topics in Artificial Intelligence (CAEPIA'07), 2007, pp. 130-139.
Rabuñal, J. R., Dorado, J., and Pazos, A., Encyclopedia of Artificial Intelligence (3 Volumes), {IGI} Global, 2009.
Pezzulo, G., Butz, M., Castelfranchi, C., Falcone, R., Baldassarre, G., Balkenius, C., Forster, A., Grinberg, M., Herbort, O., Kiryazov, K., and , Endowing Artificial Systems with Anticipatory Capabilities: Success Cases, The Challenge of Anticipation, 2008, pp. 237–254.
Balkenius, C., Pezzulo, G., Butz, V., Castelfranchi, C., Falcone, R., Baldassarre, G., Forster, A., Grinberg, M., Herbort, O., Kriyazov, K., and , Endowing Artificial Systems with Anticipatory Capabilities: Success Cases, 2008.
Bulatov, A. A., Dalmau, V., Grohe, M., and Marx, D., Enumerating homomorphisms, J. Comput. Syst. Sci., vol. 78, 2012, pp. 638-650.
Bulatov, A. A., Dalmau, V., Grohe, M., and Marx, D., Enumerating Homomorphisms, STACS, 2009, pp. 231-242.
Francès, G., and Geffner, H., E-STRIPS: Existential Quantification in Planning and Constraint Satisfaction, Proc. 25th Int. Joint Conf. on Artificial Intelligence, 2016.
Jonsson, A., Johns, J., Mehranian, H., Arroyo, I., Woolf, B., Barto, A., Fisher, D., and Mahadevan, S., Evaluating the Feasibility of Learning Student Models from Data, Proceedings of the Workshop on Educational Data Mining at AAAI'05, 2005, pp. 1-6.
Rankothge, W., Le, F., Russo, A., and Lobo, J., Experimental results on the use of genetic algorithms for scaling virtualized network functions, Network Function Virtualization and Software Defined Network (NFV-SDN), 2015 IEEE Conference on, IEEE, 2015, pp. 47–53.
Sani, A., Neu, G., and Lazaric, A., Exploiting easy data in online optimization, Advances in Neural Information Processing Systems 27 (NIPS), 2014, pp. 810-818.
Neu, G., Explore no more: Improved high-probability regret bounds for non-stochastic bandits, Advances in Neural Information Processing Systems 28 (NIPS), 2015.

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