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Journals

  1. Daniel H. Stolfi and Grégoire Danoy. Evolutionary swarm formation: From simulations to real world robots. In: Engineering Applications of Artificial Intelligence, vol. 128, pp. 107501, 2024.

    doi> 10.1016/j.engappai.2023.107501 | [BibTex]
  2. Daniel H. Stolfi and Grégoire Danoy. Design and analysis of an E-Puck2 robot plug-in for the ARGoS simulator. In: Robotics and Autonomous Systems, vol. 164, pp. 104412, 2023.

    doi> 10.1016/j.robot.2023.104412 | [BibTex] | [Files]
  3. Daniel H. Stolfi and Grégoire Danoy. Optimising Robot Swarm Formations by Using Surrogate Models and Simulations. In: Applied Sciences, vol. 13, No. 10, 2023.

    doi> 10.3390/app13105989 | [BibTex] | [Files]
  4. Daniel H. Stolfi and Matthias R. Brust and Grégoire Danoy and Pascal Bouvry. SuSy-EnGaD: Surveillance System Enhanced by Games of Drones. In: Drones, vol. 6, No. 1, 2022.

    doi> 10.3390/drones6010013 | [BibTex] | [Files]
  5. Daniel H. Stolfi and Grégoire Danoy. An Evolutionary Algorithm to Optimise a Distributed UAV Swarm Formation System. In: Applied Sciences, vol. 12, No. 20, 2022.

    doi> 10.3390/app122010218 | [BibTex]
  6. Daniel H. Stolfi and Matthias R. Brust and Grégoire Danoy and Pascal Bouvry. UAV-UGV-UMV Multi-Swarms for Cooperative Surveillance. In: Frontiers in Robotics and AI, vol. 8, 2021.

    doi> 10.3389/frobt.2021.616950 | [BibTex]
  7. Daniel H. Stolfi and Matthias R. Brust and Grégoire Danoy and Pascal Bouvry. CONSOLE: intruder detection using a UAV swarm and security rings. In: Swarm Intelligence, vol. 15, No. 3, pp. 205-235, 2021.

    doi> 10.1007/s11721-021-00193-7 | [BibTex]
  8. Matthias R. Brust and Grégoire Danoy and Daniel H. Stolfi and 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]
  9. 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, pp. 107566, 2021.

    doi> 10.1016/j.asoc.2021.107566 | [BibTex]
  10. Daniel H. Stolfi and Matthias R. Brust and Grégoire Danoy and Pascal Bouvry. A competitive Predator–Prey approach to enhance surveillance by UAV swarms. In: Applied Soft Computing, vol. 111, pp. 107701, 2021.

    doi> 10.1016/j.asoc.2021.107701 | [BibTex] | [Files]
  11. Daniel H. Stolfi and 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, vol. 27, No. 4, pp. 27-41, 2020.

    doi> 10.1080/10630732.2019.1586223 | [BibTex] | [Files]
  12. Daniel H. Stolfi and Matthias R. Brust and 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]
  13. Daniel H. Stolfi and Enrique Alba. Epigenetic algorithms: A New way of building GAs based on epigenetics. In: Information Sciences, vol. 424, No. Supplement C, pp. 250-272, 2018.

    doi> 10.1016/j.ins.2017.10.005 | [BibTex] | [Files1] | [Files2]
  14. 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]
  15. 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]
  16. 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]

Conference Proceedings

  1. Daniel H. Stolfi and Grégoire Danoy. Evaluating Surrogate Models for Robot Swarm Simulations. In: Optimization and Learning, Cham: Springer Nature Switzerland, 2023, pp. 224-235.

    doi> 10.1007/978-3-031-34020-8_17 | [BibTex] | [Slides]
  2. Daniel H. Stolfi and Grégoire Danoy. Spacecraft Swarm Orbital Formation Optimisation Using Evolutionary Techniques. In: Proceedings of the Companion Conference on Genetic and Evolutionary Computation, in GECCO '23 Companion. New York, NY, USA: Association for Computing Machinery, 2023, pp. 771–774.

    doi> 10.1145/3583133.3590651 | [BibTex] | [Slides]
  3. Daniel H. Stolfi and Grégoire Danoy. Optimising Autonomous Robot Swarm Parameters for Stable Formation Design. In: Proceedings of the Genetic and Evolutionary Computation Conference, in GECCO '22. New York, NY, USA: Association for Computing Machinery, 2022, pp. 1281–1289.

    doi> 10.1145/3512290.3528709 | [BibTex] | [Slides]
  4. Daniel H. Stolfi and Matthias R. Brust and Grégoire Danoy and Pascal Bouvry. Optimising Pheromone Communication in a UAV Swarm. In: Proceedings of the Genetic and Evolutionary Computation Conference Companion, in GECCO '21. New York, NY, USA: Association for Computing Machinery, 2021, pp. 323–324.

    doi> 10.1145/3449726.3459526 | [BibTex] | [Slides]
  5. Daniel H. Stolfi and Matthias R. Brust and Grégoire Danoy and Pascal Bouvry. Improving Pheromone Communication for UAV Swarm Mobility Management. In: Computational Collective Intelligence, Cham: Springer International Publishing, 2021, pp. 228-240.

    doi> 10.1007/978-3-030-88081-1_17 | [BibTex] | [Slides]
  6. Daniel H. Stolfi and Matthias R. Brust and Grégoire Danoy and Pascal Bouvry. A Cooperative Coevolutionary Approach to Maximise Surveillance Coverage of UAV Swarms. In: 2020 IEEE 17th Annual Consumer Communications Networking Conference (CCNC), 2020, pp. 1-6.

    doi> 10.1109/CCNC46108.2020.9045643 | [BibTex] | [Slides]
  7. Daniel H. Stolfi and Matthias R. Brust and Grégoire Danoy and Pascal Bouvry. Optimizing the Performance of an Unpredictable UAV Swarm for Intruder Detection. In: Optimization and Learning, Cham: Springer International Publishing, 2020, pp. 37-48.

    doi> 10.1007/978-3-030-41913-4_4 | [BibTex] | [Slides]
  8. Daniel H. Stolfi and M. R. Brust and 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]
  9. Andrés Camero and Jamal Toutouh and Daniel H. Stolfi and Enrique Alba. Evolutionary Deep Learning for Car Park Occupancy Prediction in Smart Cities. In: Learning and Intelligent Optimization, Cham: Springer International Publishing, 2019, pp. 386-401.

    doi> 10.1007/978-3-030-05348-2_32 | [BibTex]
  10. C. Alcaraz and E. Abdo-Sánchez and J. Toutouh and R. Halir and M. Ruiz and Daniel H. Stolfi. Some Ingredients to Improve Gamification in Engineering. In: EDULEARN18 Proceedings, in 10th International Conference on Education and New Learning Technologies. IATED, 2018, pp. 7040-7044.

    doi> 10.21125/edulearn.2018.1662 | [BibTex]
  11. Daniel H. Stolfi and Christian Cintrano and Francisco Chicano and Enrique Alba. Natural Evolution Tells Us How to Best Make Goods Delivery: Use Vans. In: Proceedings of the Genetic and Evolutionary Computation Conference Companion, in GECCO '18. New York, NY, USA: ACM, 2018, pp. 308-309.

    doi> 10.1145/3205651.3205764 | [BibTex] | [Slides]
  12. Daniel H. Stolfi and Christian Cintrano and Francisco Chicano and Enrique Alba. An Intelligent Advisor for City Traffic Policies. In: Advances in Artificial Intelligence, Cham: Springer International Publishing, 2018, pp. 383–393.

    doi> 10.1007/978-3-030-00374-6_36 | [BibTex]
  13. C Alcaraz and E Abdo and R Halir and J Toutouh and M Ruiz and Daniel H. Stolfi. Gamification to Fight Lack of Motivation and Heterogeneity in Engineering. In: EDULEARN17 Proceedings, in 9th International Conference on Education and New Learning Technologies. IATED, 2017, pp. 3662-3668.

    doi> 10.21125/edulearn.2017.1794 | [BibTex]
  14. 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, in GECCO '17. New York, NY, USA: ACM, 2017, pp. 1240-1247.

    doi> 10.1145/3071178.3071193 | [BibTex] | [Slides]
  15. Daniel H. Stolfi and 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, Proceedings, Cham: Springer International Publishing, 2017, pp. 107-117.

    doi> 10.1007/978-3-319-59513-9_11 | [BibTex] | [Slides]
  16. Christian Cintrano and Daniel H. Stolfi and Jamal Toutouh and Francisco Chicano and Enrique Alba. CTPATH: A Real World System to Enable Green Transportation by Optimizing Environmentaly Friendly Routing Paths. In: Smart Cities: First International Conference, Smart-CT 2016, Málaga, Spain, June 15-17, 2016, Proceedings, Cham: Springer International Publishing, 2016, pp. 63-75.

    doi> 10.1007/978-3-319-39595-1_7 | [BibTex]
  17. Daniel H. Stolfi and Rolando Armas and Enrique Alba and 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, in GECCO '16. New York, NY, USA: ACM, 2016, pp. 1013-1019.

    doi> 10.1145/2908812.2908868 | [BibTex] | [Slides] | [Files]
  18. Daniel H. Stolfi and Enrique Alba. Smart Mobility Policies with Evolutionary Algorithms. In: Proceedings of the 2015 on Genetic and Evolutionary Computation Conference, in GECCO '15. New York, NY, USA: ACM, 2015, pp. 1287-1294.

    doi> 10.1145/2739480.2754742 | [BibTex] | [Slides]
  19. 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, in MAEB 2015. Mérida - Almendralejo: 2015, pp. 27-34.

    [BibTex] | [Slides]
  20. Daniel H. Stolfi and Enrique Alba. An Evolutionary Algorithm to Generate Real Urban Traffic Flows. In: Advances in Artificial Intelligence, in Lecture Notes in Computer Science. Cham: Springer International Publishing, 2015, pp. 332-343.

    doi> 10.1007/978-3-319-24598-0_30 | [BibTex] | [Slides]
  21. Daniel H. Stolfi and Enrique Alba. Eco-friendly Reduction of Travel Times in European Smart Cities. In: Proceedings of the 2014 Conference on Genetic and Evolutionary Computation, in GECCO '14. New York, NY, USA: ACM, 2014, pp. 1207-1214.

    doi> 10.1145/2576768.2598317 | [BibTex] | [Slides] | [Files]
  22. 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, in GECCO '13. New York, NY, USA: ACM, 2013, pp. 1373-1380.

    doi> 10.1145/2463372.2463540 | [BibTex] | [Slides] | [Files]
  23. Daniel H. Stolfi and Enrique Alba. Reducing Gas Emissions in Smart Cities by Using the Red Swarm Architecture. In: Advances in Artificial Intelligence, in Lecture Notes in Computer Science. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013, pp. 289-299.

    doi> 10.1007/978-3-642-40643-0_30 | [BibTex] | [Slides] | [Files]

Books and Chapters

  1. Daniel H. Stolfi and Enrique Alba. Chapter 14 - Sustainable Road Traffic Using Evolutionary Algorithms. In: Sustainable Transportation and Smart Logistics, Elsevier, 2019, pp. 361-380.

    doi> 10.1016/B978-0-12-814242-4.00014-4 | [BibTex]
  2. Daniel H. Stolfi and Sergio Gálvez Rojas. CoMVeT - Control Mental de Vehículos Teledirigidos. 2011, p. 130.

    [BibTex] | [Files]
  3. Daniel H. Stolfi and Sergio Gálvez Rojas. Mundos Virtuales 3D con VRML97. 2010, p. 160.

    [BibTex] | [Files]
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