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revistas

  1. Daniel H. Stolfi, Matthias R. Brust, Grégoire Danoy, and Pascal Bouvry. A competitive Predator-Prey approach to enhance surveillance by UAV swarms. In: Applied Soft Computing, vol. 111, p. 107701, 2021.
    doi> 10.1016/j.asoc.2021.107701 | [BibTeX]
  2. Daniel H. Stolfi and Enrique Alba. Yellow Swarm: LED panels to advise optimal alternative tours to drivers in the city of Malaga. In: Applied Soft Computing, vol. 109, p. 107566, 2021.
    doi> 10.1016/j.asoc.2021.107566 | [BibTeX] | [Files]
  3. Daniel H. Stolfi, Matthias R. Brust, Grégoire Danoy, and Pascal Bouvry. CONSOLE: intruder detection using a UAV swarm and security rings. In: Swarm Intelligence, 15, 205–235, 2021.
    doi> 10.1007/s11721-021-00193-7 | [BibTeX]
  4. Matthias R. Brust, Grégoire Danoy, Daniel H. Stolfi, Pascal Bouvry. Swarm-based counter UAV defense system. In: Discover Internet of Things, vol. 1, no. 1, 2021.
    doi> 10.1007/s43926-021-00002-x | [BibTeX]
  5. Daniel H. Stolfi, Matthias R. Brust, Grégoire Danoy, and Pascal Bouvry. UAV-UGV-UMV Multi-Swarms for Cooperative Surveillance. In: Frontiers in Robotics and AI, vol. 8, Feb. 2021.
    doi> 10.3389/frobt.2021.616950 | [BibTeX]
  6. Daniel H. Stolfi, Matthias R. Brust, Grégoire Danoy, and Pascal Bouvry. Emerging Inter-Swarm Collaboration for Surveillance Using Pheromones and Evolutionary Techniques. In: Sensors, vol. 20, no. 9, 2020.
    doi> 10.3390/s20092566 | [BibTeX]
  7. Daniel H. Stolfi, Enrique Alba, and Xin Yao. Can I Park in the City Center? Predicting Car Park Occupancy Rates in Smart Cities. In: Journal of Urban Technology, 27:4, 27-41, 2020.
    doi> 10.1080/10630732.2019.1586223 | [BibTeX] | [Files]
  8. Daniel H. Stolfi and Enrique Alba. Green Swarm: Greener Routes with Bio-inspired Techniques. In: Applied Soft Computing, vol. 71, pp. 952-963, 2018.
    doi> 10.1016/j.asoc.2018.07.032 | [BibTeX] | [Files]
  9. Daniel H. Stolfi and Enrique Alba. Generating Realistic Urban Traffic Flows with Evolutionary Techniques. In: Engineering Applications of Artificial Intelligence, vol. 75, pp. 36-47, 2018.
    doi> 10.1016/j.engappai.2018.07.009 | [BibTeX] | [Files]
  10. Daniel H. Stolfi and Enrique Alba. Epigenetic algorithms: A New way of building GAs based on epigenetics. In: Information Sciences, vol. 424, Supplement C, pp. 250-272, 2018.
    doi> 10.1016/j.ins.2017.10.005 | [BibTeX] | [Files]
  11. Daniel H. Stolfi and Enrique Alba. Red Swarm: Reducing Travel Times in Smart Cities by Using Bio-inspired Algorithms. In: Applied Soft Computing, vol. 24, pp. 181-195, 2014.
    doi> 10.1016/j.asoc.2014.07.014 | [BibTeX]

libros y capítulos

  1. Daniel H. Stolfi and Enrique Alba. Chapter 14 - Sustainable Road Traffic Using Evolutionary Algorithms. In: Sustainable Transportation and Smart Logistics, Elsevier, 361-380, Eds: Faulin, Javier, Grasman, Scott E., Juan, Angel A., Hirsch, Patrick, 2019.
    doi> 10.1016/B978-0-12-814242-4.00014-4 | [BibTeX]

congresos y conferencias

  1. Daniel H. Stolfi, Matthias R. Brust, Grégoire Danoy, Pascal Bouvry. Improving Pheromone Communication for UAV Swarm Mobility Management. In: Computational Collective Intelligence, Cham, 2021, pp. 228–240.
    doi> 10.1007/978-3-030-88081-1_17 | [BibTeX]
  2. Daniel H. Stolfi, Matthias R. Brust, Grégoire Danoy, and Pascal Bouvry. Optimising pheromone communication in a UAV swarm. In: Proceedings of the Genetic and Evolutionary Computation Conference Companion, Lille, France, 2021, pp. 323–324.
    doi> 10.1145/3449726.3459526 | [BibTeX]
  3. D. H. Stolfi, M. R. Brust, G. Danoy, and P. Bouvry. Competitive Evolution of a UAV Swarm for Improving Intruder Detection Rates. In: 2020 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 2020, pp. 528–535.
    doi> 10.1109/IPDPSW50202.2020.00094 | [BibTeX] | [Slides]
  4. D. H. Stolfi, M. R. Brust, G. Danoy, and P. Bouvry. Optimizing the Performance of an Unpredictable UAV Swarm for Intruder Detection. In: Optimization and Learning, 2020, pp. 37-48.
    doi> 10.1007/978-3-030-41913-4_4 | [BibTeX] | [Slides]
  5. D. H. Stolfi, M. R. Brust, G. Danoy, and P. Bouvry. A Cooperative Coevolutionary Approach to Maximise Surveillance Coverage of UAV Swarms. In: 2020 IEEE 17th Annual Consumer Communications Networking Conference (CCNC), Las Vegas, NV, USA, 2020, pp. 1-6.
    doi> 10.1109/CCNC46108.2020.9045643 | [BibTeX] | [Slides]
  6. A. Camero, J. Toutouh, D. H. Stolfi, and E. Alba. Evolutionary Deep Learning for Car Park Occupancy Prediction in Smart Cities. In: International Conference on Learning and Intelligent Optimization, 2019, pp. 386-401.
    doi> 10.1007/978-3-030-05348-2_32 | [BibTeX]
  7. D. H. Stolfi, C. Cintrano, F. Chicano, and E. Alba. An Intelligent Advisor for City Traffic Policies. In: Advances in Artificial Intelligence, Springer International Publishing, 2018, pp. 383-393.
    doi> 10.1007/978-3-030-00374-6_36 | [BibTeX]
  8. D. H. Stolfi, C. Cintrano, F. Chicano, and E. Alba. Natural Evolution Tells Us How to Best Make Goods Delivery: Use Vans. In: Proceedings of the Genetic and Evolutionary Computation Conference Companion, GECCO ’18. ACM, 2018, pp. 308-309.
    doi> 10.1145/3205651.3205764 | [BibTeX] | [Slides]
  9. C. Alcaraz, E. Abdo-Sánchez, J. Toutouh, R. Halir, M. Ruiz, and D. H. Stolfi. Some Ingredients to Improve Gamification in Engineering. In: EDULEARN18 Proceedings, 2018, pp. 7040-7044.
    doi> 10.21125/edulearn.2018.1662 | [BibTeX]
  10. Daniel H. Stolfi and Enrique Alba. Computing New Optimized Routes for GPS Navigators Using Evolutionary Algorithms. In: Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2017, ACM, 2017, pp. 1240-1247.
    doi> 10.1145/3071178.3071193 | [BibTeX] | [Slides]
  11. C. Alcaraz, E. Abdo, R. Halir, J. Toutouh, M. Ruiz, and D. H. Stolfi. Gamification to Fight Lack of Motivation and Heterogeneity in Engineering. In: EDULEARN17 Proceedings, 2017, pp. 3662-3668.
    doi> 10.21125/edulearn.2017.1794 | [BibTeX]
  12. Daniel H. Stolfi, Enrique Alba, and Xin Yao. Predicting Car Park Occupancy Rates in Smart Cities. In: Smart Cities: Second International Conference, Smart-CT 2017, Málaga, Spain, June 14-16, 2017, pp. 107–117.
    doi> 10.1007/978-3-319-59513-9_11 | [BibTeX] | [Slides]
  13. Daniel H. Stolfi, Rolando Armas, Enrique Alba, Hernan Aguirre, and Kiyoshi Tanaka. Fine Tuning of Traffic in Our Cities with Smart Panels: The Quito City Case Study. In: Proceedings of the Genetic and Evolutionary Computation Conference 2016, GECCO 2016, ACM, 2016, pp. 1013-1019.
    doi> 10.1145/2908812.2908868 | [BibTeX] | [Slides] | [Files]
  14. C. Cintrano, D. H. Stolfi, J. Toutouh, F. Chicano, and E. Alba. CTPATH: A Real World System to Enable Green Transportation by Optimizing Environmentally Friendly Routing Paths. In: Smart Cities: First International Conference, Smart-CT 2016, Málaga, Spain, June 15-17, 2016, Proceedings, Springer International Publishing, 2016, pp. 63-75.
    doi> 10.1007/978-3-319-39595-1_7 | [BibTeX]
  15. Daniel H. Stolfi and Enrique Alba. An Evolutionary Algorithm to Generate Real Urban Traffic Flows. In: Advances in Artificial Intelligence, volume 9422 of Lecture Notes in Computer Science, Springer International Publishing, 2015, pp. 332-343.
    doi> 10.1007/978-3-319-24598-0_30 | [BibTeX] | [Slides]
  16. Daniel H. Stolfi and Enrique Alba. Smart Mobility Policies with Evolutionary Algorithms: The Adapting Info Panel Case. In: Proceedings of the 2015 on Genetic and Evolutionary Computation Conference, GECCO 2015, ACM, 2015, pp. 1287-1294.
    doi> 10.1145/2739480.2754742 | [BibTeX] | [Slides] | [Files]
  17. Daniel H. Stolfi and Enrique Alba. Un Algoritmo Evolutivo para la Reducción de Tiempos de Viaje y Emisiones Utilizando Paneles LED. In: X Congreso Español sobre Metaheurísticas, Algoritmos Evolutivos y Bioinspirados, MAEB 2015, 2015, pp. 27-34.
    [BibTeX] | [Slides]
  18. Daniel H. Stolfi and Enrique Alba. Eco-friendly Reduction of Travel Times in European Smart Cities. In: Proceeding of the Sixteenth Annual Conference on Genetic and Evolutionary Computation Conference, GECCO'14, ACM, 2014, pp. 1207-1214.
    doi> 10.1145/2576768.2598317 | [BibTeX] | [Slides] | [Files]
  19. Daniel H. Stolfi and Enrique Alba. Reducing Gas Emissions in Smart Cities by Using the Red Swarm Architecture. In: Advances in Artificial Intelligence, volume 8109 of Lecture Notes in Computer Science, Springer Berlin Heidelberg, 2013, pp. 289-299.
    doi> 10.1007/978-3-642-40643-0_30 | [BibTeX] | [Slides] | [Files]
  20. Daniel H. Stolfi and Enrique Alba. Red Swarm: Smart Mobility in Cities with EAs. In: Proceeding of the Fifteenth Annual Conference on Genetic and Evolutionary Computation Conference, GECCO'13, ACM, 2013, pp. 1373-1380.
    doi> 10.1145/2463372.2463540 | [BibTeX] | [Slides] | [Files]
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