Per anno

@incollection{agenttoolkit-eumas2025,
    abstract = {Intelligent agents have been a cornerstone of Artificial Intelligence (AI) since its early days—and received significant attention in the 1990s when the notion of autonomous agent was established, giving rise to research on Engineering Multi-Agent Systems (EMAS). Traditionally, this area has focused on theories, architectures, methodologies, paradigms, and languages for designing, implementing, and governing systems of autonomous agents. More recently, advances in Generative AI—and specifically large language models—have led to a new generation of agents and multi-agent systems, often referred to as Agentic AI. However, the conceptual bridges, overlaps, and complementarities between Agentic AI and traditional EMAS research are often unclear. The Agent Toolkits 2025 community session invited positions statements from senior members of the EMAS community to discuss these recent developments. This paper summarizes and integrates their contributions and outlines key directions for research on EMAS with Generative AI.},
    apice = {AgenttoolkitEumas2025},
    author = {Andrei Ciortea and Katharine Beaumont and Gianluca Aguzzi and Matteo Baldoni and Cristina Baroglio and Amit K. Chopra and Ciatto, Giovanni and Rem W. Collier and Mehdi Dastani and Angelo Ferrando and Andrea Gatti and Gürcan, Önder and Timotheus Kampik and Jérémy Lemée and Somsakun Maneerat and Elisa Marengo and Viviana Mascardi and Simon Mayer and Roberto Micalizio and Guillaume Muller and Vivek Nallur and Richard Niamke and Andrei Olaru and Heloise Pajot and Chloé Petridis and I. S. W. B. Prasetya and Ricci, Alessandro and Alexandru Sorici and Stefano Tedeschi and Michael Winikoff},
    booktitle = {Multi-Agent Systems: 22nd European Conference, EUMAS 2025, Bucharest, Romania, September 3–5, 2025, Proceedings, Part I},
    dblp = {conf/eumas/CiorteaBABBCCCDFGGKLMMM25.bib},
    doi = {10.1007/978-3-032-22817-8_22},
    editor = {Matteo Baldoni and Franziska Klügl and Andrei Olaru and Alexandru Sorici and Adina Magda Florea},
    keywords = {Engineering Multi-Agent Systems, Generative AI, Agent Toolkits},
    pages = {379--401},
    publisher = {Springer},
    series = {Lecture Notes in Computer Science},
    subseries = {Lecture Notes in Artificial Intelligence},
    title = {Engineering Multi-agent Systems and Generative {AI:} Report from the Agent Toolkits 2025 Community Session},
    url = {https://link.springer.com/10.1007/978-3-032-22817-8_22},
    urlpdf = {https://link.springer.com/content/pdf/10.1007/978-3-032-22817-8_22.pdf},
    volume = 16258,
    year = 2025
}

@article{llmoracles-kbs310,
    acm = {10.1016/j.knosys.2024.112940},
    apice = {LlmoraclesKbs310},
    articleno = 112940,
    arxiv = {2404.04108},
    author = {Ciatto, Giovanni and Agiollo, Andrea and Magnini, Matteo and Omicini, Andrea},
    dblp = {journals/kbs/CiattoAMO25},
    doi = {10.1016/j.knosys.2024.112940},
    iris = {11585/1001205},
    issn = {0950-7051},
    journal = {Knowledge-Based Systems},
    keywords = {Ontology population; Large language models; Nutrition; Automation; Domain-specific knowledge},
    lens = {002-808-574-876-090},
    month = {15~} # feb,
    numpages = 22,
    openalex = {W4406141444},
    opencitations = {0606112740},
    pages = {1--22},
    publisher = {Elsevier B.V.},
    scholar = {12608317221311042342},
    scopus = {2-s2.0-85214522484},
    title = {Large language models as oracles for instantiating ontologies with domain-specific knowledge},
    url = {https://www.sciencedirect.com/science/article/pii/S0950705124015740},
    urlopenaccess = {https://www.sciencedirect.com/science/article/pii/S0950705124015740},
    volume = 310,
    wos = {WOS:001397431800001},
    year = 2025
}

@book{extraamas2025,
    apice = {Extraamas2025},
    dblp = {conf/extraamas/2025},
    doi = {10.1007/978-3-032-01399-6},
    editor = {Davide Calvaresi and Amro Najaar and Omicini, Andrea and Reyhan Aydogan and Rachele Carli and Ciatto, Giovanni and Simona Tiribelli and Kary Främling},
    eisbn = {978-3-032-01399-6},
    eissn = {1611-3349},
    iris = {11585/1048535},
    isbn = {978-3-032-01398-9},
    issn = {0302-9743},
    keywords = {Multi-Agent Systems, Computing most probable explanation, Machine Learning, Law, Social and Behavioral Sciences, Artificial Intelligence, Knowledge Representation and Reasoning, Rule Learning},
    lens = {152-897-082-698-933},
    month = oct,
    openalex = {W4414994966},
    publisher = {Springer},
    scholar = {9214865659693901175},
    series = {Lecture Notes in Computer Science},
    subseries = {Lecture Notes in Artificial Intelligence},
    subtitle = {7th International Workshop, EXTRAAMAS 2025, Detroit, MI, USA, May 19–20, 2025, Revised Selected Papers},
    title = {Explainable, Trustworthy, and Responsible AI and Multi-Agent Systems},
    url = {https://link.springer.com/10.1007/978-3-032-01398-9},
    urlpdf = {https://link.springer.com/content/pdf/10.1007/978-3-032-01398-9.pdf},
    volume = 15939,
    year = 2025
}

@book{eumas2024,
    apice = {Eumas2024},
    dblp = {conf/eumas/2024},
    doi = {10.1007/978-3-031-93930-3},
    editor = {Collier, Rem and Ricci, Alessandro and Nallur, Vivek and Burattini, Samuele and Omicini, Andrea},
    eisbn = {978-3-031-93930-3},
    eissn = {1611-3349},
    iris = {11585/1018534},
    isbn = {978-3-031-93929-7},
    issn = {0302-9743},
    lens = {165-692-867-243-675},
    month = jun,
    openalex = {W4411449911},
    publisher = {Springer},
    scholar = {15937114239578467962},
    series = {Lecture Notes in Computer Science},
    subseries = {Lecture Notes in Artificial Intelligence},
    subtitle = {21st European Conference, EUMAS 2024, Dublin, Ireland, August 26–28, 2024, Proceedings},
    title = {Multi-Agent Systems},
    url = {https://link.springer.com/10.1007/978-3-031-93930-3},
    urlpdf = {https://link.springer.com/content/pdf/10.1007/978-3-031-93930-3.pdf},
    volume = 15685,
    year = 2025
}

@article{pfander2025,
    apice = {Pfander2025},
    author = {Pfänder, Jan and Altay, Sacha},
    doi = {10.1038/s41562-024-02086-1},
    journal = {Nature Human Behaviour},
    month = apr,
    pages = {688--699},
    title = {Spotting False News and Doubting True News: A Systematic Review and Meta-Analysis of News Judgements},
    url = {https://www.nature.com/articles/s41562-024-02086-1},
    urlopenaccess = {https://www.nature.com/articles/s41562-024-02086-1.pdf},
    urlpdf = {https://www.nature.com/articles/s41562-024-02086-1.pdf},
    volume = 9,
    year = 2025
}

@inproceedings{digitalutopia-woa2025,
    apice = {DigitalutopiaWoa2025},
    articleno = 7,
    author = {Sara Hejazi and Daniele Franch and Pierluigi Roberti and Enrico Blanzieri},
    booktitle = {WOA 2025 -- 26th Workshop ``From Objects to Agents'':},
    editor = {Ciatto, Giovanni and Enrico Blanzieri and Viviana Mascardi},
    issn = {1613-0073},
    keywords = {Large Language Models (LLMs), social actors, digital utopia, conflicts, concealment},
    location = {Trento, TN, Italy},
    month = {set},
    numpages = 16,
    pages = {90--105},
    publisher = {Sun SITE Central Europe, RWTH Aachen University},
    series = {CEUR Workshop Proceedings},
    subseries = {AIxIA Series},
    title = {From Conflict to Concealment: The Role of Generative AI in Creating a Digital Utopia},
    url = {https://ceur-ws.org/Vol-4028/paper7.pdf},
    urlopenaccess = {https://ceur-ws.org/Vol-4028/paper7.pdf},
    volume = 4028,
    year = 2025
}

@incollection{fairbridge-hiccs2025,
    apice = {FairnessHicss2025},
    author = {Ciatto, Giovanni and Matteini, Mattia and Laura Sartori and Maria Rebrean and Catelijne Muller and Andrea Borghesi and Calegari, Roberta},
    booktitle = {Proceedings of the 58th Hawaii International Conference on System Sciences},
    doi = {10.24251/HICSS.2025.777},
    iris = {11585/1018911},
    isbn = {978-0-9981331-8-8},
    keywords = {AI and Digital Discrimination, artificial intelligence, bias, design, fairness, multi-disciplinarity},
    location = {Hawaii, HI, USA},
    numpages = 10,
    openalex = {w4407208122},
    pages = {6504--6513},
    scholar = {5084539886289942855},
    scopus = {2-s2.0-105005142003},
    title = {{AI}-fairness: the {FAIRBRIDGE} approach to practically bridge the gap between socio-legal and technical perspectives},
    url = {https://hdl.handle.net/10125/109625},
    wos = {WOS:001443246900761},
    year = 2025
}

@book{encyclopediabioinformaticscomputationalbiology2025,
    apice = {EncyclopediaBioinformaticsComputationalBiology2025},
    editor = {Shoba Ranganathan and Mario Cannataro and Mohammad Asif Khan},
    eisbn = {9780323955034},
    isbn = {9780323955027},
    month = jun,
    publisher = {Elsevier},
    title = {Encyclopedia of Bioinformatics and Computational Biology, 2nd Edition},
    url = {https://www.sciencedirect.com/referencework/9780323955034/encyclopedia-of-bioinformatics-and-computational-biology},
    year = 2025
}

@inproceedings{plangenerationbdi-ecai2025,
    abstract = {Extending BDI agents with the ability to autonomously generate plans has long been a goal in the field of cognitive agent engineering to enhance their adaptability. Recent advances in GenAI are now opening new possibilities for plan generation, by leveraging the natural-language understanding, mean-end reasoning, and abstraction capabilities of LLMs. In this paper, we investigate the integration of GenAI-based plan generation into AgentSpeak(L) agents, and we analyse the implications of transferring knowledge between the LLM and the BDI agent, for the sake of dynamic plan generation. We propose a coherent framework where AgentSpeak(L) is extended with plan generation, and we model the boundaries of the generative process. We prototype our framework via the JaKtA BDI agent technology, and we methodologically assess the quality of the plans generated by LLMs of different sorts.},
    apice = {PlanGenerationBDIEcai2025},
    author = {Ciatto, Giovanni and Aguzzi, Gianluca and Battistini, Riccardo and Baiardi, Martina and Samuele Burattini and Ricci, Alessandro},
    booktitle = {28th European Conference on Artificial Intelligence, 25-30 October 2025, Bologna, Italy – Including 14th Conference on Prestigious Applications of Intelligent Systems (PAIS 2025)},
    doi = {10.3233/FAIA251223},
    editor = {Inês Lynce and Nello Murano and Mauro Vallati and Serena Villata and Chesani, Federico and Milano, Michela and Omicini, Andrea and Mehdi Dastani},
    keywords = {belief desire intention, BDI, multi-agent systems, planning, GenAI, LLM},
    numpages = 8,
    openalex = {W4415428067},
    pages = {3495--3502},
    publisher = {IOS Press},
    series = {Frontiers in Artificial Intelligence and Applications},
    title = {Exploiting GenAI for Plan Generation in BDI Agents},
    type = {InProceedings},
    url = {https://ebooks.iospress.nl/doi/10.3233/FAIA251223},
    urlopenaccess = {https://ebooks.iospress.nl/doi/10.3233/FAIA251223},
    volume = 413,
    year = 2025
}

@inproceedings{chatbdi-aamas2025,
    apice = {ChatbdiAamas2025},
    author = {Gatti, Andrea and Mascardi, Viviana and Ferrando, Angelo},
    booktitle = {28th European Conference on Artificial Intelligence, 25-30 October 2025, Bologna, Italy -- Including 14th Conference on Prestigious Applications of Intelligent Systems (PAIS 2025)},
    doi = {10.3233/FAIA251242},
    editor = {Lynce, Inês and Murano, Nello and Vallati, Mauro and Villata, Serena and Chesani, Federico and Milano, Michela and Omicini, Andrea and Dastani, Mehdi},
    isbn = {978-1-64368-631-8},
    keywords = {bdi, beliefs-desires-intentions, chatbdi, chattification, domain independent, general purpose, large language models, llm},
    numpages = 9,
    pages = {2541--2543},
    publisher = {IOS Press},
    series = {Frontiers in Artificial Intelligence and Applications Ebook},
    title = {Let Me Talk to You! Natural Language Interaction Between Humans and {BDI} Agents via {ChatBDI}},
    url = {https://ebooks.iospress.nl/doi/10.3233/FAIA251242},
    urlpdf = {https://dl.acm.org/doi/epdf/10.5555/3709347.3743930},
    volume = 413,
    year = 2025
}

@inproceedings{aequitas24bellatreccia,
    abstract = {AI-based diagnosis of skin diseases holds considerable promise for increasing healthcare accessibility, however, its effectiveness is currently limited by several challenges, including fairness. This study analyzes a real-world dataset collected from an Italian hospital, characterized by limited data availability, leading to poor diversity and representation—particularly evident in the scarcity of data for certain diseases and darker skin tones. Such limitations result in substantial classification biases. Additionally, the dataset includes non-dermoscopic, consumer-grade images that suffer from quality issues like inconsistent lighting and blurriness, complicating the training of fair and efficient AI models. Conventional strategies to mitigate these problems, such as synthesizing images for underrepresented groups, are hindered by the difficulty in accurately identifying skin tones from poor-quality images. Our research introduces a novel pipeline designed to enhance both the accuracy and fairness of skin disease diagnosis by addressing the challenges posed by real-world data. The proposed solution involves a two-stage approach: 1) data pre-processing and augmentation to obtain images that more accurately represent darker skin tones, generated through a state-of-the-art diffusion model; and 2) disease classification employing deep learning models. This methodology addresses data scarcity and improves fairness, with thorough validation of real-world data showing enhanced reliability and fairness in predictions across various skin diseases.},
    apice = {Aequitas24Bellatreccia},
    author = {Chiara Bellatreccia and Daniele Zama and Arianna Dondi and Luca Pierantoni and Andreozzi Laura and Iria Neri and Marcello Lanari and Andrea Borghesi and Calegari, Roberta},
    booktitle = {Proceedings of the 2nd Workshop on AI bias: Measurements, Mitigation, Explanation Strategies},
    iris = {11585/1018912},
    publisher = {CEUR Workshop Proceedings},
    title = {Addressing Bias and Data Scarcity in AI-Based Skin Disease Diagnosis with Non-Dermoscopic Images},
    url = {https://ceur-ws.org/Vol-3961/paper8.pdf},
    venue = {Barcelona, Spain},
    volume = 3961,
    year = 2025
}

@proceedings{woa2025,
    apice = {Woa2025},
    editor = {Ciatto, Giovanni and Enrico Blanzieri and Viviana Mascardi},
    issn = {1613-0073},
    location = {Trento, TN, Italy},
    month = {set},
    publisher = {Sun SITE Central Europe, RWTH Aachen University},
    series = {CEUR Workshop Proceedings},
    subseries = {AIxIA Series},
    title = {WOA 2025 – 26th Workshop ``From Objects to Agents''},
    url = {https://ceur-ws.org/Vol-4028/},
    urlopenaccess = {https://ceur-ws.org/Vol-4028/},
    volume = 4028,
    year = 2025
}

@proceedings{aamas2025,
    booktitle = {Proceedings of the 2025 International Conference on Autonomous Agents and Multiagent Systems},
    editor = {Sanmay Das and Ann Nowé and Yevgeniy Vorobeychik},
    isbn = {979-8-4007-1426-9},
    issn = {2523-5699},
    note = {24th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2025), Detroit, MI, USA, 19-23 May 2025},
    publisher = {IFAAMAS},
    title = {Proceedings of the 2025 International Conference on Autonomous Agents and Multiagent Systems},
    url = {https://www.ifaamas.org/Proceedings/aamas2025/},
    year = 2025
}

@incollection{intagenv-envencyclopediabio2025,
    apice = {IntagenvEncyclopediaBio2025},
    author = {Alfredo Garro and Alberto Falcone and Matteo Baldoni and Cristina Baroglio and Federico Bergenti and Mariani, Stefano and Omicini, Andrea and Giuseppe Vizzari},
    booktitle = {Encyclopedia of Bioinformatics and Computational Biology, 2nd Edition},
    doi = {10.1016/B978-0-323-95502-7.00039-7},
    editor = {Shoba Ranganathan and Mario Cannataro and Mohammad Asif Khan},
    iris = {11585/1024252},
    isbn = {978-0-323-95503-4},
    keywords = {Artificial systems, Autonomy cooperation, Biological systems, Environment, Intelligent agent, Natural systems},
    lens = {101-781-749-172-055},
    month = jun,
    numpages = 7,
    openalex = {W4400166517},
    pages = {372--378},
    publisher = {Elsevier},
    scopus = {2-s2.0-105030220300},
    title = {Intelligent Agents and Environment},
    url = {https://www.sciencedirect.com/science/article/pii/B9780323955027000397},
    volume = 1,
    year = 2025
}

@proceedings{ecai2025,
    apice = {Ecai2025},
    dblp = {conf/ecai/2025},
    doi = {10.3233/faia413},
    editor = {Lynce, Inês and Murano, Nello and Vallati, Mauro and Villata, Serena and Chesani, Federico and Milano, Michela and Omicini, Andrea and Dastani, Mehdi},
    iris = {11585/1049667},
    isbn = {9781643686318},
    lens = {042-445-554-735-267},
    numpages = 5508,
    openalex = {W4415428967},
    publisher = {IOS Press},
    series = {Frontiers in Artificial Intelligence and Applications},
    title = {28th European Conference on Artificial Intelligence, 25-30 October 2025, Bologna, Italy – Including 14th Conference on Prestigious Applications of Intelligent Systems (PAIS 2025)},
    url = {https://ebooks.iospress.nl/doi/10.3233/FAIA413},
    volume = 413,
    year = 2025
}

@inproceedings{agentsvsllmspanelwoa2025-eumas2025,
    apice = {Agentsvsllmspanelwoa2025Eumas2025},
    author = {Aguzzi, Gianluca and Ciatto, Giovanni and Angelo Ferrando and Andrea Gatti and Viviana Mascardi},
    booktitle = {Agent Toolkits Community Session @ EUMAS 2025, Informal Proceedings},
    location = {Bucharest, Romania},
    month = {3~} # sep,
    title = {{LLMs} as Agents, {LLMs} at the Service of Agents, or Agents at the Service of {LLMs}?},
    url = {https://interactions.ics.unisg.ch/agent-toolkits-2025/papers/aguzzi-et-al.pdf},
    year = 2025
}

@inproceedings{activelylearning-ecai2025,
    abstract = {In active learning, a learner attempts to learn from a teacher by posing questions. The questions made by the learner are called membership queries and are answered with `yes' or `no'. This kind of query is often studied as part of a communication protocol that also includes equivalence queries. Intuitively, equivalence queries ask whether the idea of the learner about the knowledge of the teacher is correct or not. If not, then the teacher should provide a counterexample showing the difference. Here, we consider the teacher as a large language model (LLM) and study the case in which knowledge is expressed as an EL terminology. Membership queries ask whether concept inclusions are true or not. E.g., ``Can algae be considered a subcategory of plant?''. Equivalence queries are simulated by a sample with concept inclusions labelled as positive or negative. We present a non-trivial extension of the ExactLearner tool to extract EL terminologies from LLMs. Given the relevant symbols as input (e.g., algae, plant, etc.), the tool tries to find how these symbols should be logically connected by posing questions to LLMs. To evaluate the approach, we present performance results of the ExactLearner in the task of reconstructing existing EL terminologies.},
    apice = {ActivelylearningEcai2025},
    author = {Magnini, Matteo and Squarcialupi, Riccardo and Martin T. Sterri and Ana Ozaki},
    booktitle = {28th European Conference on Artificial Intelligence, 25-30 October 2025, Bologna, Italy – Including 14th Conference on Prestigious Applications of Intelligent Systems (PAIS 2025)},
    doi = {10.3233/FAIA251009},
    editor = {Inês Lynce and Nello Murano and Mauro Vallati and Serena Villata and Chesani, Federico and Milano, Michela and Omicini, Andrea and Mehdi Dastani},
    isbn = {978-1-64368-631-8},
    numpages = 8,
    openalex = {W4415428417},
    pages = {1792--1799},
    publisher = {IOS Press},
    series = {Frontiers in Artificial Intelligence and Applications},
    title = {Actively Learning EL Terminologies from Large Language Models},
    url = {https://ebooks.iospress.nl/doi/10.3233/FAIA251009},
    urlopenaccess = {https://ebooks.iospress.nl/doi/10.3233/FAIA251009},
    volume = 413,
    year = 2025
}

@inproceedings{chatbdi-ecai2025,
    apice = {ChatbdiEcai2025},
    author = {Gatti, Andrea and Mascardi, Viviana and Ferrando, Angelo},
    booktitle = {28th European Conference on Artificial Intelligence, 25-30 October 2025, Bologna, Italy -- Including 14th Conference on Prestigious Applications of Intelligent Systems (PAIS 2025)},
    doi = {10.3233/FAIA251242},
    editor = {Lynce, Inês and Murano, Nello and Vallati, Mauro and Villata, Serena and Chesani, Federico and Milano, Michela and Omicini, Andrea and Dastani, Mehdi},
    isbn = {978-1-64368-631-8},
    numpages = 9,
    pages = {3646--3654},
    publisher = {IOS Press},
    series = {Frontiers in Artificial Intelligence and Applications Ebook},
    title = {Let Me Talk to You! Natural Language Interaction Between Humans and {BDI} Agents via {ChatBDI}},
    url = {https://ebooks.iospress.nl/doi/10.3233/FAIA251242},
    volume = 413,
    year = 2025
}

@inproceedings{lorawan-picom2025,
    apice = {LorawanPicom2025},
    author = {Russo, Miriana and Santoro, Corrado and Santoro, Federico Fausto and Tudisco, Alessio},
    booktitle = {23rd IEEE Conference on Pervasive and Intelligent Computing (PICom 2025)},
    doi = {10.1109/PICom68402.2025.00019},
    ieee = {11324054},
    isbn = {979-8-3315-9092-5},
    keywords = {Internet of Things, LoRa, smart cities, indoor location},
    month = {21--24~} # oct,
    pages = {97--104},
    title = {Enhancing {LoRaWAN} Simulator for Real-World Integration and Research Experimentation},
    url = {https://www.computer.org/csdl/proceedings-article/picom/2025/909200a097},
    year = 2025
}

@article{privacypreserving-smhealth36,
    abstract = {Medical chatbots are becoming a basic component in telemedicine, propelled by advancements in Large Language Models (LLMs). However, LLMs' integration into clinical settings comes with several issues, with privacy concerns being particularly significant. The paper proposes a tailored architectural solution and an information workflow that address privacy issues, while preserving the benefits of LLMs. We examine two solutions to prevent the disclosure of sensitive information: (i) a filtering mechanism that processes sensitive data locally but leverage a robust OpenAI's online LLM for engaging with the user effectively, and (ii) a fully local deployment of open-source LLMs. The effectiveness of these solutions is assessed in the context of hypertension management across various tasks, ranging from intent recognition to reliable and emphatic conversation. Interestingly, while the first solution proved to be more robust in intent recognition, an evaluation by domain experts of the models' responses, based on reliability and empathetic principles, revealed that two out of six open LLMs received the highest scores. The study underscores the viability of incorporating LLMs into medical chatbots. In particular, our findings suggest that open LLMs can offer a privacy-preserving, yet promising, alternative to external LLM services, ensuring safer and more reliable telemedicine practices. Future efforts will focus on fine-tuning local models to enhance their performance across all tasks.},
    apice = {PrivacypreservingSmhealth36},
    articleno = 100552,
    author = {Montagna, Sara and Stefano Ferretti and Lorenz Cuno Klopfenstein and Michelangelo Ungolo and Martino Francesco Pengo and Aguzzi, Gianluca and Magnini, Matteo},
    doi = {10.1016/j.smhl.2025.100552},
    eissn = {2352-6491},
    issn = {2352-6483},
    journal = {Smart Health},
    keywords = {Large Language Model, Medical chatbot, Patient self-management, Patient empowerment},
    month = mar,
    numpages = 13,
    openalex = {W4408237661},
    publisher = {Elsevier Inc.},
    title = {Privacy-preserving LLM-based chatbots for hypertensive patient self-management},
    url = {https://www.sciencedirect.com/science/article/pii/S2352648325000133},
    urlopenaccess = {https://www.sciencedirect.com/science/article/pii/S2352648325000133},
    volume = 36,
    year = 2025
}

@inproceedings{ske-aixia2024,
    abstract = {Adopting opaque machine learning predictors, which achieve very high predictive performance, often necessitates incorporating symbolic knowledge-extraction techniques. These techniques aim to explain the opaque predictions, thus making them applicable in high-stakes scenarios. The development of symbolic knowledge-extraction procedures is evolving alongside the dynamic machine learning landscape. However, there are recurring drawbacks that tend to be overlooked or addressed in a suboptimum way. Common examples include the non-exhaustiveness of the global explanations generated for a black-box predictor or the unwanted discretisation introduced in the prediction of continuous variables. To tackle these challenges, in this work, we introduce the HEx algorithm, its formalisation and its properties. This algorithm aims to obtain a symbolic, hierarchical representation of the knowledge acquired by opaque machine learning classifiers and regressors, always ensuring knowledge exhaustiveness and avoiding any output discretisation. Experiments demonstrating the superior capabilities of HEx compared to state-of-the-art competitors in terms of predictive performance, completeness, and human readability are presented.},
    apice = {SkeAixia2024},
    author = {Sabbatini, Federico and Calegari, Roberta},
    booktitle = {Advances in Artificial Intelligence},
    doi = {10.1007/978-3-031-80607-0_20},
    iris = {11585/1018918},
    keywords = {Explainable artificial intelligence, Symbolic knowledge extraction, PSyKE},
    publisher = {Springer, Cham},
    series = {Lecture Notes in Computer Science},
    subseries = {AIxIA 2024},
    title = {Hierarchical Knowledge Extraction from Opaque Machine Learning Predictors},
    url = {https://link.springer.com/10.1007/978-3-031-80607-0_20},
    volume = 15450,
    year = 2025
}

@inproceedings{dslnesy-ansya2025,
    apice = {DslNesyAnsya2025},
    author = {Matteini, Mattia and Ciatto, Giovanni and Magnini, Matteo and Kuru, Emre and Aydo{\u g}an, Reyhan and Omicini, Andrea},
    booktitle = {ANSyA 2025: Advanced Neuro-Symbolic Applications},
    dblp = {conf/ansya/MatteiniCMKAO25},
    editor = {Agiollo, Andrea and Bardhi, Enkeleda and Ciatto, Giovanni and Dumancic, Giovanni and Marra, Giuseppe},
    iris = {11585/1048553},
    keywords = {symbolic knowledge injection, SKI-lang, NeSy, language, Python},
    month = oct,
    note = {Proceedings of the 1st International Workshop on Advanced Neuro-Symbolic Applications co-located with the 28th European Conference on Artificial Intelligence (ECAI 2025)},
    numpages = 9,
    pages = {84--92},
    publisher = {CEUR-WS},
    scholar = {5084539886289942855},
    scopus = {2-s2.0-105038978909},
    series = {CEUR Workshop Proceedings},
    title = {A Domain-Specific Language for {NeSy} Focussing on Symbolic Knowledge Injection},
    url = {https://ceur-ws.org/Vol-4125/paper_21.pdf},
    urlopenaccess = {https://ceur-ws.org/Vol-4125/paper_21.pdf},
    urlpdf = {https://ceur-ws.org/Vol-4125/paper_21.pdf},
    volume = 4125,
    wos = {WOS:001664416600013},
    year = 2025
}

@inproceedings{preface-ecai2025,
    apice = {PrefaceEcai2025},
    author = {Lynce, Inês and Murano, Nello and Vallati, Mauro and Villata, Serena and Chesani, Federico and Milano, Michela and Omicini, Andrea and Dastani, Mehdi},
    booktitle = {28th European Conference on Artificial Intelligence, 25-30 October 2025, Bologna, Italy -- Including 14th Conference on Prestigious Applications of Intelligent Systems (PAIS 2025)},
    editor = {Lynce, Inês and Murano, Nello and Vallati, Mauro and Villata, Serena and Chesani, Federico and Milano, Michela and Omicini, Andrea and Dastani, Mehdi},
    iris = {11585/1049667},
    isbn = {9781643686318},
    numpages = 2,
    pages = {v--vi},
    publisher = {IOS Press},
    scopus = {2-s2.0-105024408642},
    series = {Frontiers in Artificial Intelligence and Applications},
    title = {Preface},
    url = {https://ebooks.iospress.nl/doi/10.3233/FAIA413},
    volume = 413,
    year = 2025
}

@inproceedings{nesyaichronicdiseasetelmed2025,
    apice = {NeSyAIChronicDiseaseTelmed2025},
    author = {Magnini, Matteo and Ciatto, Giovanni and Ahmet Emre Kuru and Christel Sirocchi and Montagna, Sara},
    booktitle = {2025 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)},
    doi = {10.1109/PerComWorkshops65533.2025.00106},
    editor = {Piero Castoldi and Anna Lina Ruscelli and Lorenzo Mucchi and Matti Hämäläinen},
    isbn = {979-8-3315-3553-7},
    keywords = {Symbolic Knowledge Injection, Neurosymbolic AI, Clinical protocols and data},
    month = {17-21 March},
    note = {4th International Workshop on Telemedicine and e-Health evolution in the new era of social distancing (TELMED 2025)},
    pages = {446--451},
    publisher = {IEEE},
    title = {Neuro-Symbolic AI for Supporting Chronic Disease Diagnosis and Monitoring},
    url = {https://ieeexplore.ieee.org/document/11038535},
    urlpdf = {https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11038535},
    year = 2025
}

@incollection{skemetrics-aixia2024,
    apice = {SkemetricsAixia2024},
    author = {Sabbatini, Federico and Calegari, Roberta},
    doi = {10.1007/978-3-031-80607-0_19},
    iris = {11585/1018915},
    keywords = {Explainable artificial intelligence, Symbolic knowledge extraction, AutoML},
    numpages = 16,
    pages = {241--256},
    title = {ICE: An Evaluation Metric to Assess Symbolic Knowledge Quality},
    url = {https://link.springer.com/10.1007/978-3-031-80607-0_19},
    year = 2025
}

@misc{delaflor-iainews25072025,
    abstract = {The Enlightenment ideal of objective truth is challenged, arguing that our models create reality rather than represent it. This perspective, known as Model Dependent Ontology, suggests that changing models results in fundamentally different universes. The pursuit of a single, objective truth is seen as a dangerous fantasy, leading to confusion, dogma, and violence throughout history.},
    apice = {DelaflorIainews2025},
    author = {Delaflor, Manuel},
    howpublished = {IAI News},
    month = jul,
    organization = {The Institute of Art and Ideas},
    title = {Truth Is the Most Dangerous Fantasy Our Species Ever Invented},
    url = {https://iai.tv/articles/truth-is-the-most-dangerous-fantasy-our-species-ever-invented-auid-3263},
    year = 2025
}

@inproceedings{democle-picom2025,
    apice = {DemoclePicom2025},
    author = {Bonanno, Mario and Russo, Miriana and Santoro, Corrado and Santoro, Federico Fausto and Tudisco, Alessio},
    booktitle = {23rd IEEE Conference on Pervasive and Intelligent Computing (PICom 2025)},
    doi = {10.1109/PICom68402.2025.00056},
    ieee = {11324040},
    isbn = {979-8-3315-9092-5},
    keywords = {Internet of Things, LoRa, smart cities, indoor location},
    month = {21--24~} # oct,
    pages = {315--320},
    title = {{BDI}-Driven Indoor Positioning and Assistance via Hermes Mesh Networks and LLM Interfaces},
    url = {https://www.computer.org/csdl/proceedings-article/picom/2025/909200a315},
    year = 2025
}

@incollection{intagmas-encyclopediabio2025,
    apice = {IntagmasEncyclopediaBio2025},
    author = {Alfredo Garro and Alberto Falcone and Matteo Baldoni and Cristina Baroglio and Federico Bergenti and Mariani, Stefano and Omicini, Andrea and Giuseppe Vizzari},
    booktitle = {Encyclopedia of Bioinformatics and Computational Biology, 2nd Edition},
    doi = {10.1016/B978-0-323-95502-7.00040-3},
    editor = {Shoba Ranganathan and Mario Cannataro and Mohammad Asif Khan},
    iris = {11585/1024253},
    isbn = {978-0-323-95503-4},
    keywords = {Agent-oriented, Agents multi-agent, Autonomous systems, Distributed systems, Modeling and simulation, Software engineering, Systems agent-based},
    lens = {061-459-726-231-37X},
    month = jun,
    numpages = 7,
    openalex = {W4400166535},
    pages = {379--385},
    publisher = {Elsevier},
    scopus = {2-s2.0-105030224232},
    title = {Intelligent Agents: Multi-Agent Systems},
    url = {https://www.sciencedirect.com/science/article/pii/B9780323955027000403},
    volume = 1,
    year = 2025
}

@incollection{eumas2024-preface,
    apice = {Eumas2024Preface},
    author = {Collier, Rem and Ricci, Alessandro and Nallur, Vivek and Burattini, Samuele and Omicini, Andrea},
    doi = {10.1007/978-3-031-93930-3},
    editor = {Collier, Rem and Ricci, Alessandro and Nallur, Vivek and Burattini, Samuele and Omicini, Andrea},
    eisbn = {978-3-031-93930-3},
    eissn = {1611-3349},
    iris = {11585/1019495},
    isbn = {978-3-031-93929-7},
    issn = {0302-9743},
    keywords = {Distributed Artificial Intelligence • Multi-Agent Systems • Intelligent Agent • Modelling and Simulation • Verification and Model Checking • Higher-Order Logic • Game Theory • Development Frameworks • Social Choice • Norms • Machine Ethics • Autonomous Agents • Reinforcement Learning • Simulation Environments • Agent Communication Languages • Behavioral Modeling},
    month = jun,
    pages = {v--vi},
    publisher = {Springer},
    scopus = {2-s2.0-105009322293},
    series = {Lecture Notes in Computer Science},
    subseries = {Lecture Notes in Artificial Intelligence},
    subtitle = {21st European Conference, EUMAS 2024, Dublin, Ireland, August 26–28, 2024, Proceedings},
    title = {Multi-Agent Systems},
    url = {https://link.springer.com/10.1007/978-3-031-93930-3},
    volume = 15685,
    year = 2025
}

@incollection{preface-extraamas2025,
    apice = {PrefaceExtraamas2025},
    author = {Calvaresi, Davide and Najaar, Amro and Omicini, Andrea and Främling, Kary},
    booktitle = {Explainable, Trustworthy, and Responsible AI and Multi-Agent Systems. 7th International Workshop, EXTRAAMAS 2025, Detroit, MI, USA, May 19–20, 2025, Revised Selected Papers},
    editor = {Calvaresi, Davide and Najaar, Amro and Omicini, Andrea and Aydogan, Reyhan and Carli, Rachele and Ciatto, Giovanni and Tiribelli, Simona and Främling, Kary},
    eisbn = {978-3-032-01399-6},
    eissn = {1611-3349},
    iris = {11585/1048530},
    isbn = {978-3-032-01398-9},
    issn = {0302-9743},
    month = oct,
    numpages = 2,
    pages = {v--vi},
    publisher = {Springer},
    scopus = {2-s2.0-105020094471},
    series = {Lecture Notes in Computer Science},
    subseries = {Lecture Notes in Artificial Intelligence},
    title = {Preface},
    urlpdf = {https://link.springer.com/content/pdf/bfm:978-3-032-01399-6/1},
    volume = 15939,
    year = 2025
}