@article{unfairinequality-scidata,
abstract = {This paper introduces a novel benchmark dataset designed to support fairness-oriented research in artificial intelligence within the educational domain. The dataset originates from longitudinal survey data collected by the Agencia Canaria de Calidad Universitaria y Evaluación Educativa, encompassing comprehensive information from students, families, and teachers across the Canary Islands, Spain. It includes detailed student profiles and academic trajectories, covering multiple years of academic performance outcomes. The original data is characterised by a high-dimensional and sparse feature space, which presents challenges for direct application in AI workflows. To address these challenges while minimising the risk of introducing bias during preprocessing, we provide a curated version of the dataset specifically tailored for AI applications. This version preserves the statistical properties of the original data and is accompanied by detailed documentation of the preprocessing steps, including strategies for dimensionality reduction and fairness preservation. The dataset is intended as a resource for the research community, enabling studies on fairness, predictive modeling, and educational analytics. We describe its structure, content, and preparation process.},
apice = {UnfairinequalityScidata},
articleno = 572,
author = {Joseph Giovanelli and Magnini, Matteo and Ciatto, Giovanni and Angel S. Marrero and Andrea Borghesi and Gustavo A. Marrero and Calegari, Roberta},
doi = {10.1038/s41597-026-06827-x},
issn = {2052-4463},
journal = {Scientific Data},
month = mar,
note = {Data Descriptor},
numpages = 12,
openalex = {W7133213904},
publisher = {Nature Portfolio / Springer Nature},
pubmed = {41771897},
title = {Unfair Inequality in Education: A Benchmark for AI-Fairness Research},
url = {https://doi.org/10.1038/s41597-026-06827-x},
urlopenaccess = {https://doi.org/10.1038/s41597-026-06827-x},
volume = 13,
year = 2026
}@article{bdidesimulation-jaamas40,
abstract = {Multi-agent systems are designed to deal with open, distributed systems with unpredictable dynamics, which makes them inherently hard to test. The value of using simulation for this purpose is recognized in the literature, although achieving sufficient fidelity (i.e., the degree of similarity between the simulation and the real-world system) remains a challenging task. This is exacerbated when dealing with cognitive agent models, such as the Belief Desire Intention (BDI) model, where the agent codebase is not suitable to run unchanged in simulation environments, thus increasing the reality gap between the deployed and simulated systems. We argue that BDI developers should be able to test in simulation the same specification that will be later deployed, with no surrogate representations. Thus, in this paper, we discuss how the control flow of BDI agents can be mapped onto a Discrete Event Simulation (DES), showing that such integration is possible at different degrees of granularity. We substantiate our claims by producing an open-source prototype integration between two pre-existing tools (JaKtA and Alchemist), showing that it is possible to produce a simulation-based testing environment for distributed BDI agents, and that different granularities in mapping BDI agents over DESs may lead to different degrees of fidelity.},
apice = {BdidesimulationJaamas40},
articleno = 18,
author = {Martina Baiardi and Samuele Burattini and Ciatto, Giovanni and Pianini, Danilo},
dblp = {journals/aamas/BaiardiBCP26.bib},
doi = {10.1007/S10458-026-09744-W},
journal = {Autonomous Agents and Multi-Agent Systems},
keywords = {BDI agents, BDI models, Beliefs-desires-intentions, Multi-agent systems engineering, Discrete event simulation, Software testing},
number = 1,
title = {Testing {BDI}-based multi-agent systems using discrete event simulation},
url = {https://doi.org/10.1007/s10458-026-09744-w},
volume = 40,
year = 2026
}@article{DBLP:journals/envsoft/HermosillaWWCCCGBF26,
author = {Txomin Hermosilla and
Michael A. Wulder and
Joanne C. White and
Nicholas C. Coops and
Daniel Coelho and
Giovanni Ciatto and
Noel Gorelick and
Emma Bambagioni and
Saverio Francini},
title = {Composite2Change {(C2C)} on Google Earth Engine: Time-series change
detection and metrics characterizing disturbance and recovery},
journal = {Environ. Model. Softw.},
volume = {204},
pages = {107082},
year = {2026},
url = {https://doi.org/10.1016/j.envsoft.2026.107082},
doi = {10.1016/J.ENVSOFT.2026.107082},
timestamp = {Wed, 09 Sep 2026 18:14:13 +0200},
biburl = {https://dblp.org/rec/journals/envsoft/HermosillaWWCCCGBF26.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
@incollection{neurosymbolic-woa25y,
address = {Cham},
apice = {NeurosymbolicWoa25Y},
author = {Agiollo, Andrea and Calegari, Roberta and Ciatto, Giovanni and Magnini, Matteo and Omicini, Andrea and Sabbatini, Federico},
booktitle = {The Agents Journey: Twenty-Five Years of Multi-agent Systems},
chapter = 12,
doi = {10.1007/978-3-032-22940-3_12},
editor = {Mascardi, Viviana and Omicini, Andrea},
eisbn = {978-3-032-22940-3},
eissn = {1611-3349},
iris = {11585/1061411},
isbn = {978-3-032-22939-7},
issn = {0302-9743},
keywords = {Rational Agents, Logic Programming, Multi-agent Systems, Symbolic-Subsymbolic Integration},
lens = {028-851-073-271-306},
month = apr,
numpages = 20,
openalex = {W7155969644},
pages = {320--339},
publisher = {Springer Nature Switzerland},
scholar = {21797340038813643},
scopus = {2-s2.0-105041239279},
series = {Lecture Notes in Computer Science},
subseries = {State-of-the-Art Survey},
title = {Intelligent Agents from Symbolic to Neurosymbolic Systems: The Quest for Integration},
url = {https://link.springer.com/10.1007/978-3-032-22940-3_12},
urlopenaccess = {https://link.springer.com/content/pdf/10.1007/978-3-032-22940-3_12.pdf},
volume = 16395,
year = 2026
}@incollection{ageml-adbis2026,
apice = {AgemlAdbis2026},
author = {Matteini, Mattia and Magnini, Matteo and Francia, Matteo and Ciatto, Giovanni and Omicini, Andrea},
booktitle = {Advances in Databases and Information Systems: 30th European Conference, ADBIS 2026, Orl\'{e}ans, France, September 28 -- October 1, 2026, Proceedings},
chapter = 7,
editor = {Genoveva Vargas-Solar and Kostas Stefanidis and Themis Palpanas and Patrick Marcel and Mirian Halfeld-Ferrari},
eisbn = {978-3-032-39820-8},
eissn = {1611-3349},
isbn = {978-3-032-39819-2},
issn = {0302-9743},
keywords = {MLOps, Data-centric AI, Agentic AI, AutoML, LLMs},
month = sep,
numpages = 17,
pages = {83--99},
part = {Core Database Systems and Serialization},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
title = {Agentic Architecture for Data-Centric {AutoML}},
url = {https://link.springer.com/chapter/10.1007/978-3-032-39820-8_7},
urlpdf = {https://link.springer.com/content/pdf/10.1007/978-3-032-39820-8_7.pdf},
volume = 16937,
year = 2026
}@inproceedings{CDCCPV2026,
author = {Cortecchia, Angela and Domini, Davide and Ciatto, Giovanni and Casadei, Roberto and Pianini, Danilo and Viroli, Mirko},
booktitle = {2026 22nd International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT)},
doi = {10.1109/DCOSS-IoT69657.2026.00027},
keywords = {Modeling;Internet of Things;Aggregates;Elementary particles;Image sensors;Filtering;Measurement;Printing;Timing;Programming;Distributed Particle Filtering;Aggregate Computing;Aggregate Programming;Computational Fields;Distributed State Estimation;Internet of Things},
pages = {161-168},
title = {Flexible Distributed Particle Filtering for the Internet of Things via Aggregate Computing},
year = 2026
}@article{fieldvmc-complintsys12,
abstract = {The vascular morphogenesis controller (VMC) is an approach to structure development inspired by the way plants branch and distribute nutrients. It has proven useful to guide shape formation in modular robotics as well as resource distribution in hierarchically-structured organisations, such as large companies. In this work, we propose FieldVMC: a generalisation of VMC, founded on the field-based approach known as aggregate computing, which is applicable to arbitrary topologies (i.e., undirected graphs rather than trees) and supports asynchronous and decentralised execution. We redesign VMC as a field-based computation, hence enabling the emergence of organisational hierarchies out of self-organising interactions among local entities. The benefits of our approach are manifold. Being decentralised and free from topological constraints, our approach makes VMC applicable to arbitrary networks; being based on a well-known computational model, inheriting scalability, asynchronicity, and self-organising capabilities; being implemented in a functional field-based computation framework, fostering reuse and composability. To support our claims, we conduct in-silico quantitative experiments comparing FieldVMC with the original VMC. The results demonstrate that FieldVMC is a monotonic extension of VMC, offering {{{(i)}}} faster convergence, and (ii) enhanced capabilities for capturing, analyzing, and engineering novel phenomena.},
apice = {FieldvmcComplintsys12},
author = {Angela Cortecchia and Giovanni Ciatto and Roberto Casadei and Danilo Pianini},
bibsource = {dblp computer science bibliography, https://dblp.org},
dblp = {journals/comintsys/CortecchiaCCP26},
doi = {10.1007/S40747-025-02141-Y},
journal = {Complex \& Intelligent Systems},
keywords = {Pattern formation, Growth regulation, Vascular morphogenesis controller, Self-organisation, Plant-inspired computing, Aggregate computing},
number = 2,
title = {{FieldVMC}: an asynchronous model and platform for self-organising morphogenesis of artificial structures},
url = {https://doi.org/10.1007/s40747-025-02141-y},
volume = 12,
year = 2026
}
0000-0002-1841-8996