Per Year

@proceedings{proceedings-aequitas2024,
    apice = {ProceedingsAequitasEcai2024},
    editor = {Calegari, Roberta and Virginia Dignum and Barry O'Sullivan},
    iris = {11585/996783},
    publisher = {CEUR Workshop Proceedings},
    series = {AI*IA Series},
    title = {Proceedings of the 2nd Workshop on Fairness and Bias in AI co-located with 27th European Conference on Artificial Intelligence (ECAI 2024)},
    url = {https://ceur-ws.org/Vol-3808/},
    volume = 3808,
    year = 2024
}

@article{fleming2024,
    apice = {Fleming2024},
    author = {Fleming, Stephen M.},
    doi = {10.1146/annurev-psych-022423-032425},
    eissn = {1545-2085},
    issn = {0066-4308},
    journal = {Annual Review of Psychology},
    keywords = {metacognition, confidence, uncertainty, self-model, computation},
    pages = {241--268},
    title = {Metacognition and Confidence: A Review and Synthesis},
    url = {https://www.annualreviews.org/content/journals/10.1146/annurev-psych-022423-032425},
    volume = 75,
    year = 2024
}

@inproceedings{agentsarvrxria2024,
    apice = {AgentsArVrXria2024},
    author = {Andrea Pagliericci and Daniela Briola and Viviana Mascardi},
    month = oct,
    title = {Integrating Agents and Virtual & Augmented Reality: a Preliminary Analysis of Challenges and Directions},
    urlpdf = {https://drive.google.com/file/d/11__0USVSQV-VpDppdtNskyQQp7jXEwwr/view},
    year = 2024
}

@article{sijair-fairness23,
    apice = {SIJairFairness23},
    editor = {Calegari, Roberta and Andrea Aler Tubella and Virginia Dignum and Milano, Michela},
    journal = {Journal of Artificial Intelligence Research},
    keywords = {AI Fairness, AI Bias},
    title = {Fairness and Bias in AI},
    url = {https://www.jair.org/index.php/jair/SpecialTrack-FBAI},
    year = 2024
}

@article{children24,
    abstract = {Background: Pediatric dermatology represents one of the most underserved subspecialties in pediatrics. Artificial intelligence (AI) and telemedicine have become considerable in dermatology, reaching diagnostic accuracy comparable to or exceeding that of in-person visits. This work aims to review the current state of telemedicine and AI in pediatric dermatology, suggesting potential ways to address existing issues and challenges. Methods: We conducted a literature review including only articles published in the last 15 years. A total of 458 studies were identified, of which only 76 were included. Results: Most of the studies on telemedicine evaluate accuracy focused on concordance, which ranges from 70% to 89% for the most common pediatric skin diseases. Telemedicine showed the potential to manage chronic dermatological conditions in children, as well as decrease waiting times, and represents the chance for unprivileged populations to overcome barriers limiting access to medical care. The main limitations of telemedicine consist of the language barrier and the need for adequate technologies and acceptable image-quality video, which can be overcome by AI. AI-driven apps and platforms can facilitate remote consultations between pediatric dermatologists and patients or their caregivers. However, the integration of AI into clinical practice faces some challenges ranging from technical to ethical and regulatory. It is crucial to ensure that the development, deployment, and utilization of AI systems conform to the seven fundamental requirements for trustworthy AI. Conclusion: This study supplies a detailed discussion of open challenges with a particular focus on equity and ethical considerations and defining possible concrete directions.},
    apice = {Children24},
    author = {Daniele Zama and Andrea Borghesi and Alice Ranieri and Elisa Manieri and Luca Pierantoni and Laura Andreozzi and Arianna Dondi and Iria Neri and Marcello Lanari and Calegari, Roberta},
    doi = {10.3390/children11111401},
    iris = {11585/1000949},
    journal = {Children},
    publisher = {MDPI},
    title = {Perspectives and Challenges of Telemedicine and Artificial Intelligence in Pediatric Dermatology},
    url = {https://doi.org/10.3390/children11111401},
    volume = 11,
    year = 2024
}

@inproceedings{democle-picom2024,
    apice = {DemoclePicom2024},
    author = {Cauteruccio, Francesco and Russo, Miriana and Santoro, Corrado and Santoro, Federico Fausto and Tudisco, Alessio},
    booktitle = {22nd IEEE Conference on Pervasive and Intelligent Computing (PICom 2024)},
    doi = {10.1109/PICom64201.2024.00034},
    eisbn = {979-8-3315-2274-2},
    ieee = {10795384},
    isbn = {979-8-3315-2275-9},
    keywords = {Internet of Things, LoRa, smart cities, indoor location},
    month = {5--8~} # nov,
    pages = {184--189},
    title = {A Comprehensive System for Indoor Assistance and User Interaction},
    url = {https://www.computer.org/csdl/proceedings-article/picom/2024/227400a184},
    year = 2024
}

@article{skespaceresearch24,
    apice = {SkeSpaceresearch24},
    author = {Sabbatini, Federico and Catia Grimani and Calegari, Roberta},
    doi = {10.1016/j.asr.2024.04.041},
    iris = {11585/995846},
    journal = {Advances in Space Research},
    keywords = {Space interferometers, LISA, Machine learning, Explainable clustering},
    month = {July},
    number = 1,
    numpages = 13,
    pages = {505--517},
    title = {Bridging machine learning and diagnostics of the ESA LISA space mission with equation discovery via explainable artificial intelligence},
    url = {https://www.sciencedirect.com/science/article/pii/S0273117724003880},
    volume = 74,
    year = 2024
}

@incollection{skinimagesaaai2024,
    apice = {SkinimagesAaai2024},
    author = {Andrea Borghesi and Calegari, Roberta},
    booktitle = {AI for Health Equity and Fairness},
    doi = {10.1007/978-3-031-63592-2_5},
    iris = {11585/979615},
    month = {Aug},
    numpages = 18,
    pages = {47--64},
    publisher = {Springer, Cham},
    series = {Studies in Computational Intelligence},
    title = {Generation of Clinical Skin Images with Pathology with Scarce Data},
    url = {https://link.springer.com/10.1007/978-3-031-63592-2_5},
    year = 2024
}

@article{jakta-sncs2024,
    abstract = {The popularity of multi-paradigm languages is on the rise, enabling developers to select the most appropriate paradigm for each task. While object-oriented (OOP) and functional programming (FP) are commonly combined, other paradigms can also be hybridized. This paper introduces JaKtA, an internal Domain-Specific Language (DSL) designed to support the definition of BDI agents in Kotlin. Our work represents an initial exploration into blending Agent-Oriented Programming (AOP) with other prevalent paradigms, emphasizing the potential benefits of using internal DSLs. We demonstrate, through JaKtA, how this approach facilitates the creation of compact and expressive Belief-Desire-Intention (BDI) agents that seamlessly integrate with the host language, its libraries, and tooling.},
    apice = {SncsExtendedEumasJakta2024},
    author = {Baiardi, Martina and Samuele Burattini and Ciatto, Giovanni and Pianini, Danilo},
    journal = {SN Computer Science},
    keywords = {BDI, AgentSpeak(L), DSL, Kotlin, JaKtA},
    publisher = {Springer},
    title = {Blending BDI agents with object-oriented and functional programming with JaKtA},
    year = 2024
}

@article{ske-ia2024,
    apice = {SkeIa2024},
    author = {Sabbatini, Federico and Calegari, Roberta},
    doi = {10.3233/IA-240026},
    iris = {11585/995926},
    journal = {Intelligenza Artificiale},
    keywords = {Explainable clustering, explainable artificial intelligence, symbolic knowledge extraction, PSyKE},
    number = 1,
    numpages = 14,
    pages = {21--34},
    title = {Untying black boxes with clustering-based symbolic knowledge extraction},
    url = {https://journals.sagepub.com/doi/10.3233/IA-240026},
    urlpdf = {https://journals.sagepub.com/doi/pdf/10.3233/IA-240026},
    volume = 18,
    year = 2024
}

@inproceedings{masconcurrency-aamas2024,
    acm = {3663089},
    apice = {BdiconcurrencyAamas2024},
    author = {Baiardi, Martina and Burattini, Samuele and Ciatto, Giovanni and Pianini, Danilo and Ricci, Alessandro and Omicini, Andrea},
    booktitle = {AAMAS '24: Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems},
    dblp = {conf/atal/BaiardiBCPOR24},
    doi = {10.65109/kvwh6977},
    iris = {11585/973178},
    isbn = {979-8-4007-0486-4},
    keywords = {Agent-Oriented Programming; Concurrency; BDI Agents; Threads},
    lens = {192-615-822-504-026},
    month = may,
    note = {Extended abstract},
    numpages = 3,
    openalex = {W7124281729},
    pages = {2147--2149},
    publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
    scholar = {4738339792803409504},
    scopus = {2-s2.0-85196388369},
    title = {Concurrency Model of {BDI} Programming Frameworks: Why Should We Control It?},
    url = {https://dl.acm.org/doi/10.5555/3635637.3663089},
    urlopenaccess = {https://arxiv.org/abs/2404.10421},
    urlpdf = {https://dl.acm.org/doi/pdf/10.5555/3635637.3663089},
    year = 2024
}

@inproceedings{fairanki-jcai2024,
    apice = {FairankIjcai2024},
    author = {Eleonora Misino and Calegari, Roberta and Michele Lombardi and Michela Milano},
    booktitle = {Proceedings of the 33rd International Joint Conference on Artificial Intelligence AI for Good},
    doi = {10.24963/ijcai.2024/820},
    iris = {11585/984254},
    keywords = {AI Ethics, Trust, Fairness},
    numpages = 9,
    pages = {7412--7420},
    title = {Ensuring Fairness Stability for Disentangling Social Inequality in Access to Education: the FAiRDAS General Method},
    url = {https://doi.org/10.24963/ijcai.2024/820},
    urlopenaccess = {https://www.ijcai.org/proceedings/2024/0820.pdf},
    urlpdf = {https://www.ijcai.org/proceedings/2024/0820.pdf},
    venue = {IJCAI 2024},
    year = 2024
}

@proceedings{aamas2024,
    booktitle = {Proceedings of the 2024 International Conference on Autonomous Agents and Multiagent Systems},
    editor = {Mehdi Dastani and Jaime Simão Sichman and Natasha Alechina and Virginia Dignum},
    isbn = {979-8-4007-0486-4},
    issn = {2523-5699},
    note = {23rd International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2024), Auckland, New Zealand, 6-10 May 2024. The IFAAMAS proceedings page prints the ISBN as 978-1-4007-0486-4, which fails its own check digit; 979-8-4007-0486-4 is the valid form and the one recorded here.},
    publisher = {IFAAMAS},
    title = {Proceedings of the 2024 International Conference on Autonomous Agents and Multiagent Systems},
    url = {https://www.ifaamas.org/Proceedings/aamas2024/},
    year = 2024
}

@inproceedings{exact-learning-llm-dl2024,
    apice = {OntologyDL2024},
    articleno = 32,
    author = {Magnini, Matteo and Ana Ozaki and Squarcialupi, Riccardo},
    booktitle = {Proceedings of the 37th International Workshop on Description Logics {(DL} 2024), Bergen, Norway, June 18-21, 2024},
    dblp = {conf/dlog/MagniniOS24},
    editor = {Laura Giordano and Jean Christoph Jung and Ana Ozaki},
    iris = {11585/996984},
    issn = {1613-0073},
    keywords = {Active Learning, Ontologies, Language Models},
    month = jun,
    note = {Extended abstract},
    numpages = 5,
    pages = {1--5},
    publisher = {CEUR-WS.org},
    series = {{CEUR} Workshop Proceedings},
    title = {Actively Learning Ontologies from LLMs: First Results (Extended Abstract)},
    url = {https://ceur-ws.org/Vol-3739/abstract-18.pdf},
    urlopenaccess = {https://ceur-ws.org/Vol-3739/abstract-18.pdf},
    urlpdf = {https://ceur-ws.org/Vol-3739/abstract-18.pdf},
    volume = 3739,
    year = 2024
}

@inproceedings{llmbasedhealthcarechatbots-telmed2024,
    apice = {LlmBasedHealthcareChatbotsTelmed2024},
    author = {Montagna, Sara and Aguzzi, Gianluca and Ferretti, Stefano and Pengo, Martino Francesco and Klopfenstein, Lorenz Cuno and Ungolo, Michelangelo and Magnini, Matteo},
    booktitle = {2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)},
    doi = {10.1109/PerComWorkshops59983.2024.10503257},
    keywords = {large language model, medical chatbot, chronic disease management},
    numpages = 6,
    pages = {346--351},
    title = {LLM-based Solutions for Healthcare Chatbots: a Comparative Analysis},
    year = 2024
}

@inproceedings{ske-aequitas24,
    abstract = {This work explores the efficacy of symbolic knowledge-extraction (SKE) techniques in identifying biases and unfairness within opaque predictive models. Logic rules extracted from black-box predictors make it possible to verify if decisions are influenced by protected or sensitive features. In particular, the identifi- cation of biased or unfair decisions can be achieved through the evaluation of if-then rules, detecting the inclusion of protected and/or sensitive information in the rules' precondition. The effectiveness of SKE in this regard is demonstrated here by conducting various simulations on a well-known data set for loan grant prediction. Our findings highlight the potential of SKE as a valuable tool to reveal biases and discrimination in opaque predictions, ultimately contributing to the pursuit of fair and transparent decision-making systems.},
    apice = {SkeAequitas24},
    author = {Sabbatini, Federico and Calegari, Roberta},
    booktitle = {Proceedings of the 2nd Workshop on Fairness and Bias in AI co-located with 27th European Conference on Artificial Intelligence (ECAI 2024)},
    iris = {11585/1001068},
    keywords = {Fairness in AI, Bias in AI, Explainable artificial intelligence, XAI, Symbolic knowledge extraction, PSyKE},
    month = oct,
    publisher = {Sun SITE Central Europe, RWTH Aachen University},
    series = {CEUR Workshop Proceedings},
    title = {Unmasking the Shadows: Leveraging Symbolic Knowledge Extraction to Discover Biases and Unfairness in Opaque Predictive Models},
    url = {https://ceur-ws.org/Vol-3808/paper13.pdf},
    venue = {Santiago de Compostela, Spain},
    volume = 3808,
    year = 2024
}

@inproceedings{fauci-aequitas2024,
    apice = {FauciAequitas2024},
    articleno = 8,
    author = {Magnini, Matteo and Ciatto, Giovanni and Calegari, Roberta and Omicini, Andrea},
    booktitle = {AEQUITAS 2024: Fairness and Bias in AI},
    dblp = {conf/aequitas/MagniniCCO24},
    editor = {Calegari, Roberta and Dignum, Virginia and O'Sullivan, Barry},
    iris = {11585/995740},
    keywords = {AI Fairness, FaUCI, in-processing, regularization, mitigation},
    month = oct,
    note = {Proceedings of the 2nd Workshop on Fairness and Bias in AI co-located with 27th European Conference on Artificial Intelligence (ECAI 2024)},
    numpages = 13,
    pages = {1--13},
    publisher = {CEUR-WS},
    scholar = {12743200180573703475},
    scopus = {2-s2.0-85210042328},
    series = {CEUR Workshop Proceedings},
    title = {Enforcing Fairness via Constraint Injection with {FaUCI}},
    url = {https://ceur-ws.org/Vol-3808/paper8.pdf},
    urlopenaccess = {https://ceur-ws.org/Vol-3808/paper8.pdf},
    urlpdf = {https://ceur-ws.org/Vol-3808/paper8.pdf},
    volume = 3808,
    wos = {WOS:001752291200008},
    year = 2024
}

@article{skemetrics-aaai2023,
    address = {San Francisco, California},
    apice = {SkemetricsAAAISpring2023},
    author = {Sabbatini, Federico and Calegari, Roberta},
    booktitle = {AAAI 2023 Spring Symposium Series},
    doi = {10.1007/s43681-023-00406-1},
    iris = {11585/995844},
    journal = {AI and Ethics},
    keywords = {Explainable artificial intelligence; Symbolic knowledge extraction; Readability metrics; AutoML},
    month = mar,
    publisher = {Springer Nature},
    title = {On the Evaluation of the Symbolic Knowledge Extracted from Black Boxes},
    year = 2023
}

@book{extraamas2024,
    apice = {Extraamas2024},
    dblp = {conf/extraamas/2024},
    doi = {10.1007/978-3-031-70074-3},
    editor = {Calvaresi, Davide and Najaar, Amro and Omicini, Andrea and Aydogan, Reyhan and Carli, Rachele and Ciatto, Giovanni and Hulstijn, Joris and Främling, Kary},
    eisbn = {978-3-031-70074-3},
    eissn = {1611-3349},
    iris = {11585/988174},
    isbn = {978-3-031-70073-6},
    issn = {0302-9743},
    lens = {154-121-100-324-877},
    month = sep,
    openalex = {W4402782974},
    publisher = {Springer},
    scholar = {16205626934148009035},
    series = {Lecture Notes in Computer Science},
    subseries = {Lecture Notes in Artificial Intelligence},
    subtitle = {6th International Workshop, EXTRAAMAS 2024, Auckland, New Zealand, May 6–10, 2024, Revised Selected Papers},
    title = {Explainable, Transparent Autonomous Agents and Multi-Agent Systems},
    url = {https://link.springer.com/10.1007/978-3-031-70074-3},
    urlpdf = {https://link.springer.com/content/pdf/10.1007/978-3-031-70074-3.pdf},
    volume = 14847,
    year = 2024
}

@article{skeislr-csur56,
    acm = {3645103},
    apice = {SkeislrCsur56},
    articleno = 161,
    author = {Ciatto, Giovanni and Sabbatini, Federico and Agiollo, Andrea and Magnini, Matteo and Omicini, Andrea},
    dblp = {journals/csur/CiattoSAMO24},
    doi = {10.1145/3645103},
    eissn = {1557-734},
    iris = {11585/969235},
    issn = {0360-0300},
    journal = {ACM Computing Surveys},
    keywords = {Logic; Machine learning theory; Hybrid symbolic-numeric methods; Knowledge representation and reasoning},
    lens = {143-064-043-213-611},
    month = jun,
    number = 6,
    numpages = 35,
    openalex = {W4391645809},
    opencitations = {06804657002},
    pages = {1--35},
    publisher = {ACM},
    scholar = {13701373869146776438},
    scopus = {2-s2.0-85188835517},
    semanticscholar = {267611660},
    title = {Symbolic Knowledge Extraction and Injection with Sub-symbolic Predictors: A Systematic Literature Review},
    url = {https://dl.acm.org/doi/10.1145/3645103},
    urlopenaccess = {https://dl.acm.org/doi/pdf/10.1145/3645103},
    urlpdf = {https://dl.acm.org/doi/pdf/10.1145/3645103},
    volume = 56,
    wos = {WOS:001208566200027},
    year = 2024
}

@article{skenlp-jaamas38,
    apice = {SkenlpJaamas38},
    articleno = 32,
    author = {Agiollo, Andrea and Siebert, Luciano Cavalcante and Murukannaiah, Pradeep Kumar and Omicini, Andrea},
    dblp = {journals/aamas/AgiolloSMO24},
    doi = {10.1007/s10458-024-09663-8},
    iris = {11585/973894},
    journal = {Autonomous Agents and Multi-Agent Systems},
    keywords = {Natural language processing, post-hoc explanations, symbolic knowledge extraction, eXplainable AI, resource-friendly AI},
    lens = {048-322-352-133-098},
    month = jul,
    note = {Special Issue on Multi-Agent Systems and Explainable AI},
    numpages = 33,
    openalex = {W4400425589},
    pages = {1--33},
    publisher = {Springer},
    scholar = {13114388339509722903},
    scopus = {2-s2.0-85197706028},
    semanticscholar = {271083044},
    title = {From Large Language Models to Small Logic Programs: Building Global Explanations from Disagreeing Local Post-hoc Explainers},
    url = {https://link.springer.com/10.1007/s10458-024-09663-8},
    urlopenaccess = {https://link.springer.com/content/pdf/10.1007/s10458-024-09663-8.pdf},
    urlpdf = {https://link.springer.com/content/pdf/10.1007/s10458-024-09663-8.pdf},
    volume = 38,
    wos = {WOS:001264787900001},
    year = 2024
}

@incollection{preface-extraamas2024,
    apice = {PrefaceExtraamas2024},
    author = {Calvaresi, Davide and Najaar, Amro and Omicini, Andrea and Främling, Kary},
    booktitle = {Explainable, Transparent Autonomous Agents and Multi-Agent Systems. 6th International Workshop, EXTRAAMAS 2024, Auckland, New Zealand, May 6--10, 2024, Revised Selected Papers},
    editor = {Calvaresi, Davide and Najaar, Amro and Omicini, Andrea and Aydogan, Reyhan and Carli, Rachele and Ciatto, Giovanni and Hulstijn, Joris and Främling, Kary},
    eisbn = {978-3-031-70074-3},
    eissn = {1611-3349},
    iris = {11585/988176},
    isbn = {978-3-031-70073-6},
    issn = {0302-9743},
    month = sep,
    numpages = 1,
    pages = {vi},
    publisher = {Springer},
    scopus = {2-s2.0-85206104226},
    series = {Lecture Notes in Computer Science},
    subseries = {Lecture Notes in Artificial Intelligence},
    title = {Preface},
    urlpdf = {https://link.springer.com/content/pdf/bfm:978-3-031-70074-3/1},
    volume = 14847,
    year = 2024
}

@article{siacmtai23,
    apice = {SiAcmTai23},
    doi = {10.1145/3649452},
    editor = {Calegari, Roberta and Fosca Giannotti and Francesca Pratesi and Milano, Michela},
    iris = {11585/996787},
    journal = {ACM Computing Surveys},
    month = apr,
    number = 7,
    publisher = {ACM},
    title = {Special Issue on Trustworthy AI},
    url = {https://dl.acm.org/doi/10.1145/3649452},
    urlpdf = {https://dl.acm.org/pb-assets/static_journal_pages/csur/pdf/CSUR-CFP-Trustworthy-AI_083022-1661888117770.pdf},
    volume = 56,
    year = 2024
}

@inproceedings{longtermfairness-aequitas24,
    abstract = {Recent advancements have made significant progress in addressing fair ranking and fairness with continuous sensitive attributes as separate challenges. However, their intersection remains underexplored, although crucial for guaranteeing a wider applicability of fairness requirements. In many real-world contexts, sensitive attributes such as age, weight, income, or degree of disability are measured on a continuous scale rather than in discrete categories. Addressing the continuous nature of these attributes is essential for ensuring effective fairness in such scenarios. This work aims to fill the gap in the existing literature by proposing a novel methodology that integrates state-of-the-art techniques to address long- term fairness in the presence of continuous protected attributes. We demonstrate the effectiveness and flexibility of our approach using real-world data.},
    apice = {LongtermfairnessAequitas24},
    author = {Luca Giuliani and Eleonora Misino and Calegari, Roberta and Michele Lombardi},
    booktitle = {Proceedings of the 2nd Workshop on Fairness and Bias in AI co-located with 27th European Conference on Artificial Intelligence (ECAI 2024)},
    iris = {11585/998075},
    month = oct,
    title = {Long-Term Fairness Strategies in Ranking with Continuous Sensitive Attributes},
    url = {https://ceur-ws.org/Vol-3808/paper11.pdf},
    venue = {Santiago de Compostela, Spain},
    volume = 3808,
    year = 2024
}

@inproceedings{skemetrics-woa2024,
    abstract = {In multi-agent systems, understanding the similarities and differences in agents' knowledge is essential for effective decision-making, coordination, and knowledge sharing. Current similarity metrics like cosine similarity, Jaccard similarity, and BERTScore are often too generic for comparing knowledge bases, overlooking critical aspects such as overlapping and fragmented boundaries, and varying domain densities. This paper introduces new specific similarity metrics for comparing knowledge bases, represented via symbolic knowledge. Our method compares local explanations of individual instances, preserving computational resources and providing a comprehensive evaluation of knowledge similarity. This approach addresses the limitations of existing metrics, enhancing the functionality and efficiency of multi-agent systems.},
    apice = {SkemetricsWoa2024},
    author = {Sabbatini, Federico and Christel Sirocchi and Calegari, Roberta},
    booktitle = {WOA 2024 – 25th Workshop "From Objects to Agents 2024"},
    editor = {Marco Alderighi and Matteo Baldoni and Cristina Baroglio and Roberto Micalizio and Stefano Tedeschi},
    iris = {11585/995843},
    keywords = {Multi-agent systems, Knowledge similarity, Symbolic knowledge},
    title = {Symbolic Knowledge Comparison: Metrics and Methodologies for Multi-Agent Systems},
    url = {https://ceur-ws.org/Vol-3735/paper_17.pdf},
    urlpdf = {https://ceur-ws.org/Vol-3735/paper_17.pdf},
    venue = {Bard, AO, Italy},
    volume = 3735,
    year = 2024
}

@article{ndnfl-fgcs2023,
    apice = {NdnflFgcs2023},
    author = {Agiollo, Andrea and Enkeleda Bardhi and Mauro Conti and Nicolò Dal Fabbro and Riccardo Lazzeretti},
    doi = {10.1016/j.future.2023.11.009},
    issn = {0167-739X},
    journal = {Future Generation Computer Systems},
    keywords = {Anonymous communication, Federated Learning, Named Data Networking, Privacy-preserving},
    note = {Special Issue on Federated Learning on the Edge: Challenges and Future Directions},
    pages = {288--303},
    publisher = {Elsevier},
    title = {Anonymous Federated Learning via Named-Data Networking},
    url = {https://www.sciencedirect.com/science/article/pii/S0167739X23004144},
    volume = 152,
    year = 2024
}

@inproceedings{equalopportunity-aequitas24,
    abstract = {This study focuses on predicting students' academic performance, examining how AI predictive models often reflect socioeconomic inequalities influenced by factors such as parental socioeconomic status and home environ- ment, which affect the fairness of predictions. We compare three AI models aimed at performing an ablation study to understand how these sensitive features (referred to as circumstances) influence predictions. Our findings reveal biases in predictions that favor advantaged groups, depending on whether the goal is to identify excellence or underperformance. Additionally, a two-stage estimation procedure is proposed in the third model to mitigate the impact of sensitive features on predictions, thereby offering a model that can be considered fair with respect to inequality of opportunity.},
    apice = {EqualopportunityAequitas24},
    author = {Ángel S. Marrero and Gustavo A. Marrero and Carlos Bethencourt and Liam James and Calegari, Roberta},
    booktitle = {Proceedings of the 2nd Workshop on Fairness and Bias in AI co-located with 27th European Conference on Artificial Intelligence (ECAI 2024)},
    iris = {11585/1001050},
    keywords = {AI-fairness, socioeconomic equality of opportunity, AI-ethics},
    month = {Oct},
    series = {CEUR Workshop Proceedings},
    title = {AI-fairness and equality of opportunity: a case study on educational achievement},
    url = {https://ceur-ws.org/Vol-3808/paper17.pdf},
    volume = 3808,
    year = 2024
}

@inproceedings{hermes-woa2024,
    apice = {HermesWoa2024},
    author = {Carnemolla, Davide and Messina, Fabrizio and Santoro, Corrado and Santoro, Federico Fausto},
    booktitle = {WOA 2024 -- 25th Workshop ``From Objects to Agents 2024''},
    dblp = {conf/woa/CarnemollaMSS24},
    editor = {Alderighi, Marco and Baldoni, Matteo and Baroglio, Cristina and Micalizio, Roberto and Tedeschi, Stefano},
    issn = {1613-0073},
    keywords = {multi-agents, edge computing, internet of things, networks},
    location = {Bard, AO, Italy},
    month = jul,
    numpages = 9,
    pages = {33--41},
    publisher = {Sun SITE Central Europe, RWTH Aachen University},
    series = {CEUR Workshop Proceedings},
    subseries = {AIxIA Series},
    title = {Hermes: a Wireless Communication Interface for Edge Computing},
    url = {https://ceur-ws.org/Vol-3735/paper_03.pdf},
    urlopenaccess = {https://ceur-ws.org/Vol-3735/paper_03.pdf},
    urlpdf = {https://ceur-ws.org/Vol-3735/paper_03.pdf},
    volume = 3735,
    year = 2024
}

@article{eneafl-fgcs154,
    apice = {EneaflFgcs154},
    author = {Agiollo, Andrea and Bellavista, Paolo and Mendula, Matteo and Omicini, Andrea},
    dblp = {journals/fgcs/AgiolloBMO24},
    doi = {10.1016/j.future.2024.01.007},
    editor = {Hao Wu and Carlo Puliafito and Omer F. Rana and Luiz F. Bittencourt},
    iris = {11585/953081},
    issn = {0167-739X},
    journal = {Future Generation Computer Systems},
    keywords = {Serverless, Federated Learning, Energy Management, Internet of Things, Resource-constrained Learning},
    lens = {168-138-382-414-385},
    month = may,
    note = {Special Issue ``Serverless Computing in the Cloud-to-Edge Continuum''},
    numpages = 16,
    openalex = {W4390661811},
    pages = {219--234},
    publisher = {Elsevier Science B.V.},
    scholar = {15164122000920541506},
    scopus = {2-s2.0-85182399653},
    semanticscholar = {268131278},
    title = {{EneA-FL}: Energy-aware Orchestration for Serverless Federated Learning},
    url = {https://www.sciencedirect.com/science/article/pii/S0167739X24000074},
    volume = 154,
    wos = {WOS:001164533000001},
    year = 2024
}

@inproceedings{agentslargemodels-aamas2024,
    address = {Auckland, New Zealand},
    apice = {AgentslargemodelsAamas2024},
    author = {Ricci, Alessandro and Mariani, Stefano and Zambonelli, Franco and Burattini, Samuele and Castelfranchi, Cristiano},
    booktitle = {Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2024)},
    editor = {Alechina, Natasha and Dignum, Virginia and Dastani, Mehdi and Sichman, Jaime Sim{\~a}o},
    isbn = {978-1-4007-0486-4},
    month = {6--10~} # may,
    pages = {2706--2711},
    publisher = {IFAAMAS},
    title = {The Cognitive Hourglass: Agent Abstractions in the Large Models Era},
    url = {https://www.ifaamas.org/Proceedings/aamas2024/pdfs/p2706.pdf},
    urlopenaccess = {https://www.ifaamas.org/Proceedings/aamas2024/pdfs/p2706.pdf},
    urlpdf = {https://www.ifaamas.org/Proceedings/aamas2024/pdfs/p2706.pdf},
    year = 2024
}

@inproceedings{llmruleenforcement-aixhmi2024,
    apice = {LlmruleenforcementAixhmi2024},
    author = {Daniele Franch and Pierluigi Roberti and Enrico Blanzieri},
    booktitle = {AIxHMI 2024 -- 3rd Workshop on Artificial Intelligence for Human-Machine Interaction 2024},
    editor = {Aurora Saibene and Silvia Corchs and Simone Fontana and Jordi Solé-Casals},
    issn = {1613-0073},
    month = dec,
    series = {CEUR Workshop Proceedings},
    subseries = {AIxIA Series},
    title = {Rule enforcement in {LLMs}: a parameter efficient fine-tuning approach with self-generated training dataset},
    url = {https://ceur-ws.org/Vol-3903/},
    volume = 3903,
    year = 2024
}

@incollection{bdiconcurrency-emas2024,
    apice = {BdiconcurrencyEmas2024},
    author = {Baiardi, Martina and Samuele Burattini and Ciatto, Giovanni and Pianini, Danilo and Ricci, Alessandro and Omicini, Andrea},
    booktitle = {12th International Workshop, EMAS 2024, Auckland, New Zealand, May 6–7, 2024, Revised Selected Papers},
    dblp = {conf/emas/BaiardiBCPRO24},
    doi = {10.1007/978-3-031-71152-7_3},
    editor = {Briola, Daniela and Cardoso, Rafael C. and Logan, Brian},
    eisbn = {978-3-031-71152-7},
    eissn = {1611-3349},
    iris = {11585/995135},
    isbn = {978-3-031-71151-0},
    issn = {0302-9743},
    keywords = {Agent-Oriented Programming, Concurrency, BDI Agents, Threading, Parallelism},
    lens = {065-726-912-088-000},
    month = oct,
    numpages = 22,
    openalex = {W4403742469},
    pages = {42--63},
    publisher = {Springer Cham},
    scholar = {2966045943433174401},
    series = {Lecture Notes in Computer Science},
    subseries = {Lecture Notes in Artificial Intelligence},
    title = {On the External Concurrency of Current {BDI} Frameworks for {MAS}},
    url = {https://link.springer.com/10.1007/978-3-031-71152-7},
    urlopenaccess = {https://arxiv.org/abs/2404.10397},
    urlpdf = {https://link.springer.com/content/pdf/10.1007/978-3-031-71152-7_3.pdf},
    volume = 15152,
    year = 2024
}

@inproceedings{skidatadegradation-woa2024,
    apice = {SkidatadegradationWoa2024},
    author = {Rafanelli, Andrea and Magnini, Matteo and Agiollo, Andrea and Ciatto, Giovanni and Omicini, Andrea},
    booktitle = {WOA 2024 -- 25th Workshop ``From Objects to Agents 2024''},
    dblp = {conf/woa/RafanelliMACO24},
    editor = {Alderighi, Marco and Baldoni, Matteo and Baroglio, Cristina and Micalizio, Roberto and Tedeschi, Stefano},
    iris = {11585/975934},
    issn = {1613-0073},
    keywords = {Symbolic Knowledge Injection, Robustness, Neural Networks},
    location = {Bard, AO, Italy},
    month = jul,
    numpages = 13,
    pages = {20--32},
    publisher = {Sun SITE Central Europe, RWTH Aachen University},
    scholar = {9917174396528512749},
    scopus = {2-s2.0-85200118300},
    series = {CEUR Workshop Proceedings},
    subseries = {AIxIA Series},
    title = {An Empirical Study on the Robustness of Knowledge Injection Techniques Against Data Degradation},
    url = {https://ceur-ws.org/Vol-3735/paper_02.pdf},
    urlopenaccess = {https://ceur-ws.org/Vol-3735/paper_02.pdf},
    urlpdf = {https://ceur-ws.org/Vol-3735/paper_02.pdf},
    volume = 3735,
    wos = {WOS:001788634000002},
    year = 2024
}

@incollection{falconefestschrift2024-coordinationandtrust,
    apice = {Falconefestschrift2024Coordinationandtrust},
    author = {Omicini, Andrea and Ricci, Alessandro},
    booktitle = {Waves of Trust: Science, Technology and Society. Essays in Honor of Rino Falcone},
    editor = {Sapienza, Alessandro and Cantucci, Filippo and Paglieri, Fabio and Tummolini, Luca},
    iris = {11585/1000785},
    isbn = {978-1-84890-475-0},
    month = dec,
    numpages = 13,
    pages = {285--297},
    publisher = {College Publications},
    scholar = {6832642622712007880},
    series = {Tributes},
    title = {Coordination and Trust in {MAS} Towards Intelligent Socio-technical Systems},
    url = {https://www.collegepublications.co.uk/tributes/?00052},
    volume = 52,
    year = 2024
}

@inproceedings{bdiagents-cilc2024,
    apice = {BdiagentsCilc2024},
    author = {Ferrando, Angelo and Gatti, Andrea and Mascardi, Viviana},
    booktitle = {CILC 2024 -- Italian Conference on Computational Logic 2024},
    dblp = {conf/cilc/00010M24.bib},
    editor = {De Angelis, Emanuele and Proietti, Maurizio},
    publisher = {CEUR-WS.org},
    series = {CEUR Workshop Proceedings},
    title = {Geometric and Spatial Reasoning in {BDI} Agents: {A} Survey},
    url = {https://ceur-ws.org/Vol-3733/paper1.pdf},
    volume = 3733,
    year = 2024
}

@inproceedings{samis-kdd2024,
    acm = {3671985},
    apice = {SamisKdd2024},
    author = {Agiollo, Andrea and Young In Kim and Khanna, Rajiv},
    booktitle = {Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '24)},
    dblp = {conf/kdd/AgiolloKK24},
    doi = {10.1145/3637528.3671985},
    keywords = {Neural Networks, Data-efficient Learning, Memorization, Flatness},
    month = aug,
    numpages = 12,
    pages = {17--28},
    publisher = {ACM},
    scholar = {8151925308990231563},
    title = {Approximating Memorization Using Loss Surface Geometry for Dataset Pruning and Summarization},
    url = {https://dl.acm.org/doi/10.1145/3637528.3671985},
    urlopenaccess = {https://dl.acm.org/doi/pdf/10.1145/3637528.3671985},
    urlpdf = {https://dl.acm.org/doi/pdf/10.1145/3637528.3671985},
    year = 2024
}