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FEATURED CONTENTS

RESEARCH PROJECTS

ADARS

The ADARS project (Automating the Design of Autonomous Robot Swarms) aims to propose a unique solution to the design of distributed autonomous systems by addressing the following question: is it possible to automatically generate efficient and reusable behaviors for distributed aerospace and space systems (DASS)? To this end, ADARS will advance the state-of-the-art in the field of swarm robotics and automated algorithm design. Read more...

Hunted

The HUNTED project (Heterogeneous multi-swarms of UNmanned auTonomous systEms for mission Deployment) aims at designing a novel generation of mobility models for heterogeneous multi-swarms of Unmanned Autonomous Systems (UAS) for surveillance and tracking of imminent threats. Such swarms are composed of several vehicles moving in an autonomous and coordinated manner in the air, on the ground, and in the sea. Read more...

6CITY

In the 6CITY project (TIN2017-88213-R) the working hypothesis is that many different problems of smart cities (according to EU: economy, mobility, governance, people, living, environment), which are multidisciplinary in nature and ​apparently unrelated, can be solved by looking at their (possibly similar) underlying quantitative and qualitative features, as well as by providing ​advanced algorithms ​that can ​search, optimize and learn ​by themselves (to an extent) for those situations where knowledge of the problem is very limited (as it happens in many real cases). Read more...

MOVEON

The MOVEON project (TIN2014-57341-R) makes an ambitious proposal for focused research in challenges related to intelligent transport and smart mobility. We do it from the perspective of building new applications based in solver metaheuristic engines enhanced with methodologies and theories contributed by our team so as to exhibit "holistic intelligence". Read more...

MAXCT

The MAXCT project (OTRI # 8.06/5.47.4356 - AOP GGI3003IDI) consists of two parallel applications are running to improve the traffic flow in a city: HITUL - Holistic Intelligence for Traffic Urban Lights - system offers an informed support for decision-making at city level, optimizing the planning of the existing traffic lights network; and CTPATH is our second tool in this project. Drivers could receive route advices based in their preferences and city conditions, both powered to reduce the travel times and the carbon footprint. Read more...

roadME

The roadME project (TIN2011-28194) intends to characterize, design, and evaluate metaheuristic techniques able to solve real world problems, and then, particular applications of a communication network of vehicles (VANET). Our hypothesis is that standard metaheuristics are not able by themselves to address the tight requirements of many complex problems like this one, since we are dealing with execution times of a few seconds, specific user constraints, scalable to very big dimension problems, and robust to work in different scenarios. Read more...

PATIO

The Project PATIO: Collaborative Learning and User Modelling Techniques Applied to Multicultural Integration (TIC-4273), has been developed by the group of Investigation and Application of Artificial Intelligence of the Department of Computer Science and Programming Languages of the University of Málaga, subsidized by the Ministry of Innovation, Science and Business of the Andalusian Regional Government (2008 official announcement for excellence Projects). Read more...

JOURNAL PUBLICATIONS

Full List
Evolutionary swarm formation: From simulations to real world robots

Evolutionary swarm formation: From simulations to real world robots

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]
@Article{Stolfi2024,
  author   = {Daniel H. Stolfi and Gr\'{e}goire Danoy},
  journal  = {Engineering Applications of Artificial Intelligence},
  title    = {Evolutionary swarm formation: From simulations to real world robots},
  year     = {2024},
  issn     = {0952-1976},
  pages    = {107501},
  volume   = {128},
  doi      = {10.1016/j.engappai.2023.107501},
  groups   = {My Publications},
  keywords = {Swarm robotics, Evolutionary algorithm, E-Puck2, ARGoS simulator, Robot formation},
  url      = {https://www.sciencedirect.com/science/article/pii/S0952197623016858},
}
Optimising Robot Swarm Formations by Using Surrogate Models and Simulations

Optimising Robot Swarm Formations by Using Surrogate Models and Simulations

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]
@Article{Stolfi2023a,
  author         = {Stolfi, Daniel H. and Danoy, Gr\'{e}goire},
  journal        = {Applied Sciences},
  title          = {Optimising Robot Swarm Formations by Using Surrogate Models and Simulations},
  year           = {2023},
  issn           = {2076-3417},
  number         = {10},
  volume         = {13},
  article-number = {5989},
  doi            = {10.3390/app13105989},
  url            = {https://www.mdpi.com/2076-3417/13/10/5989},
}
Design and analysis of an E-Puck2 robot plug-in for the ARGoS simulator

Design and analysis of an E-Puck2 robot plug-in for the ARGoS simulator

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]
@Article{Stolfi2023,
  author   = {Daniel H. Stolfi and Gr\'{e}goire Danoy},
  journal  = {Robotics and Autonomous Systems},
  title    = {Design and analysis of an {E-Puck2} robot plug-in for the {ARGoS} simulator},
  year     = {2023},
  issn     = {0921-8890},
  pages    = {104412},
  volume   = {164},
  doi      = {10.1016/j.robot.2023.104412},
  keywords = {E-puck2, ARGoS, Computer simulations, Sensors, Swarm robotic},
  url      = {https://www.sciencedirect.com/science/article/pii/S0921889023000519},
}
An Evolutionary Algorithm to Optimise a Distributed UAV Swarm Formation System

An Evolutionary Algorithm to Optimise a Distributed UAV Swarm Formation System

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]
@Article{Stolfi2022b,
  author         = {Stolfi, Daniel H. and Danoy, Gr\'{e}goire},
  journal        = {Applied Sciences},
  title          = {An Evolutionary Algorithm to Optimise a Distributed UAV Swarm Formation System},
  year           = {2022},
  issn           = {2076-3417},
  number         = {20},
  volume         = {12},
  article-number = {10218},
  doi            = {10.3390/app122010218},
  url            = {https://www.mdpi.com/2076-3417/12/20/10218},
}
SuSy-EnGaD: Surveillance System Enhanced by Games of Drones

SuSy-EnGaD: Surveillance System Enhanced by Games of Drones

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]
@Article{drones6010013,
  AUTHOR = {Stolfi, Daniel H. and Brust, Matthias R. and Danoy, Gr\'{e}goire and Bouvry, Pascal},
  TITLE = {{SuSy-EnGaD}: Surveillance System Enhanced by Games of Drones},
  JOURNAL = {Drones},
  VOLUME = {6},
  YEAR = {2022},
  NUMBER = {1},
  ARTICLE-NUMBER = {13},
  URL = {https://www.mdpi.com/2504-446X/6/1/13},
  ISSN = {2504-446X},
  DOI = {10.3390/drones6010013},
  FILE = {https://gitlab.uni.lu/hunted/susy-engad-surveillance-system-enhanced-by-games-of-drones}
}
A competitive Predator–Prey approach to enhance surveillance by UAV swarms

A competitive Predator–Prey approach to enhance surveillance by UAV swarms

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]
@article{Stolfi2021c,
  title = {A competitive Predator–Prey approach to enhance surveillance by UAV swarms},
  journal = {Applied Soft Computing},
  volume = {111},
  pages = {107701},
  year = {2021},
  issn = {1568-4946},
  doi = {10.1016/j.asoc.2021.107701},
  author = {Daniel H. Stolfi and Matthias R. Brust and Gr\'{e}goire Danoy and Pascal Bouvry},
  keywords = {Swarm robotics, Computer simulation, Mobility model, Unmanned aerial vehicle, Competitive coevolutionary genetic algorithm},
}
Yellow Swarm: LED panels to advise optimal alternative tours to drivers in the city of Malaga

Yellow Swarm: LED panels to advise optimal alternative tours to drivers in the city of Malaga

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]
@Article{Stolfi2021b,
  author   = {Daniel H. Stolfi and Enrique Alba},
  journal  = {Applied Soft Computing},
  title    = {Yellow Swarm: LED panels to advise optimal alternative tours to drivers in the city of Malaga},
  year     = {2021},
  issn     = {1568-4946},
  pages    = {107566},
  volume   = {109},
  doi      = {10.1016/j.asoc.2021.107566},
  groups   = {My Publications},
  keywords = {epiGenetic algorithm, Smart mobility, LED panel, Travel time, Greenhouse gas emissions, Fuel consumption}
}
CONSOLE: intruder detection using a UAV swarm and security rings

CONSOLE: intruder detection using a UAV swarm and security rings

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]
@Article{Stolfi2021a,
  author    = {Daniel H. Stolfi and Matthias R. Brust and Gr{\'{e}}goire Danoy and Pascal Bouvry},
  journal   = {Swarm Intelligence},
  title     = {CONSOLE: intruder detection using a UAV swarm and security rings},
  year      = {2021},
  issn      = {1935-3820},
  number    = {3},
  pages     = {205--235},
  volume    = {15},
  doi       = {10.1007/s11721-021-00193-7},
  groups    = {My Publications},
  publisher = {Springer Science and Business Media {LLC}},
  refid     = {Stolfi2021},
  url       = {10.1007/s11721-021-00193-7},
}
Swarm-based counter UAV defense system

Swarm-based counter UAV defense system

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]
@Article{Brust2021,
  author    = {Matthias R. Brust and Gr{\'{e}}goire Danoy and Daniel H. Stolfi and Pascal Bouvry},
  journal   = {Discover Internet of Things},
  title     = {Swarm-based counter {UAV} defense system},
  year      = {2021},
  month     = {feb},
  number    = {1},
  volume    = {1},
  doi       = {10.1007/s43926-021-00002-x},
  groups    = {My Publications},
  publisher = {Springer Science and Business Media {LLC}},
}
UAV-UGV-UMV Multi-Swarms for Cooperative Surveillance

UAV-UGV-UMV Multi-Swarms for Cooperative Surveillance

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]
@article{Stolfi2021,
  author = {Stolfi, Daniel H. and Brust, Matthias R. and Danoy, Gr{\'{e}}goire and Bouvry, Pascal},
  doi = {10.3389/frobt.2021.616950},
  issn = {2296-9144},
  journal = {Frontiers in Robotics and AI},
  month = {feb},
  title = {{UAV-UGV-UMV Multi-Swarms for Cooperative Surveillance}},
  url = {https://www.frontiersin.org/articles/10.3389/frobt.2021.616950/full},
  volume = {8},
  year = {2021}
}
Emerging Inter-Swarm Collaboration for Surveillance Using Pheromones and Evolutionary Techniques

Emerging Inter-Swarm Collaboration for Surveillance Using Pheromones and Evolutionary Techniques

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]
@article{s20092566,
  author = {Stolfi, Daniel H. and Brust, Matthias R. and Danoy, Gr{\'e}goire and Bouvry, Pascal},
  title = {Emerging Inter-Swarm Collaboration for Surveillance Using Pheromones and Evolutionary Techniques},
  journal = {Sensors},
  volume = {20},
  year = {2020},
  number = {9},
  url = {https://www.mdpi.com/1424-8220/20/9/2566},
  issn = {1424-8220},
  doi = {10.3390/s20092566}
}
Can I Park in the City Center? Predicting Car Park Occupancy Rates in Smart Cities

Can I Park in the City Center? Predicting Car Park Occupancy Rates in Smart Cities

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]
@article{doi:10.1080/10630732.2019.1586223,
  author = {Stolfi, Daniel H. and Alba, Enrique and Yao, Xin},
  title = {Can I Park in the City Center? Predicting Car Park Occupancy Rates in Smart Cities},
  journal = {Journal of Urban Technology},
  volume = {27},
  number = {4},
  pages = {27-41},
  year  = {2020},
  publisher = {Routledge},
  doi = {10.1080/10630732.2019.1586223},
}
Green Swarm: Greener routes with bio-inspired techniques

Green Swarm: Greener routes with bio-inspired techniques

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]
@article{STOLFI2018952,
  title = "Green Swarm: Greener routes with bio-inspired techniques",
  journal = "Applied Soft Computing",
  volume = "71",
  pages = "952 - 963",
  year = "2018",
  issn = "1568-4946",
  doi = "10.1016/j.asoc.2018.07.032",
  url = "http://www.sciencedirect.com/science/article/pii/S1568494618304204",
  author = "Daniel H. Stolfi and Enrique Alba",
  keywords = "Evolutionary algorithm, Road traffic, Smart city, Smart mobility, Gas emissions, Wi-Fi connections",
}
Generating realistic urban traffic flows with evolutionary techniques

Generating realistic urban traffic flows with evolutionary techniques

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]
@article{STOLFI201836,
  title = "Generating realistic urban traffic flows with evolutionary techniques",
  journal = "Engineering Applications of Artificial Intelligence",
  volume = "75",
  pages = "36 - 47",
  year = "2018",
  issn = "0952-1976",
  doi = "10.1016/j.engappai.2018.07.009",
  url = "http://www.sciencedirect.com/science/article/pii/S0952197618301532",
  author = "Daniel H. Stolfi and Enrique Alba",
  keywords = "Evolutionary algorithm, Traffic simulation, Smart mobility, SUMO, Road traffic optimization, O–D matrix",
}
Epigenetic algorithms: A New way of building GAs based on epigenetics

Epigenetic algorithms: A New way of building GAs based on epigenetics

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]
@article{STOLFI2018250,
  author = {Stolfi, Daniel H. and Alba, Enrique},
  doi = {10.1016/j.ins.2017.10.005},
  issn = {0020-0255},
  journal = {Information Sciences},
  keywords = {Evolutionary algorithm; Epigenetics; MKP; Bio-insp},
  number = {Supplement C},
  pages = {250--272},
  title = {{Epigenetic algorithms: A New way of building GAs based on epigenetics}},
  url = {http://www.sciencedirect.com/science/article/pii/S0020025517309921},
  volume = {424},
  year = {2018},
}
Red Swarm: Reducing travel times in smart cities by using bio-inspired algorithms

Red Swarm: Reducing travel times in smart cities by using bio-inspired algorithms

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]
@article{Stolfi2014,
  title = "Red Swarm: Reducing travel times in smart cities by using bio-inspired algorithms",
  journal = "Applied Soft Computing",
  volume = "24",
  pages = "181 - 195",
  year = "2014",
  issn = "1568-4946",
  doi = "10.1016/j.asoc.2014.07.014",
  author = "Daniel H. Stolfi and Enrique Alba",
  keywords = "Evolutionary algorithm, Road traffic, Smart city, Smart mobility, WiFi connections, Traffic light"
}
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