[1] M. Persiani, E. Guerrero, A. Br¨annstr¨om, K. Kilic, and T. Kampik, “Fantastic argumentation tools and where to
find them,” in 5th International Workshop on Systems and Algorithms for Formal Argumentation (SAFA), 2024.
[2] M. Persiani, “Pyplaf: Probabilistic logical argumentation frameworks in python,” in 10th International Conference on Computational Models of Argument (COMMA), 2024.
[3] M. Maitreyee, M. Persiani, R. Chen, and L. Li, “Theorisehai: Shaping human-agent interactions through interdisciplinary theories,” in Proceedings of the 12th International Conference on Human-Agent Interaction, HAI ’24, (New York, NY, USA), p. 462–464, Association for Computing Machinery, 2024.
[4] H. Lindgren, V. Kaelin, A. M. Ljusb¨ack, M. Tewari, M. Persiani, and I. Nilsson, “To adapt or not to adapt — older adults enacting agency in dialogues with an unknowledgeable agent,” in 32nd ACM Conference on User Modeling, Adaptation and Personalization (UMAP), 2024.
[5] M. Persiani, H. Norberg, M. Blusi, and J. C. Nieves, “Smap: Smart personalized medication assistant to help nurses in medication adherence,” in Workshop on Intelligent Management Information Systems (IMIS @ECAI), 2023.
[6] M. Persiani, Expressing and recognizing intentions. PhD thesis, Department of Computing Science, Ume˚a University, 2022.
[7] M. Persiani and T. Hellstr¨om, “The mirror agent model: A bayesian architecture for interpretable agent behavior,” in Explainable and Transparent AI and Multi-Agent Systems (D. Calvaresi, A. Najjar, M. Winikoff, and K. Fr¨amling, eds.), (Cham), Springer International Publishing, 2022.
[8] M. Persiani and T. Hellstr¨om, “Informative communication of robot plans,” in International Conference on Practical Applications of Agents and Multi-Agent Systems (PAAMS), 2022.
[9] M. Persiani and T. Hellstr¨om, “Policy regularization for legible behavior,” Neural Computing and Applications, vol. 35, no. 23, pp. 16781–16790, 2023.
[10] M. Persiani and T. Hellstr¨om, “Policy regularization for legible behavior (extended abstract),” in Workshop on Human-aligned Reinforcement Learning for Autonomous Agents and Robots (HARL @ICRA), 2021.
[11] M. Tewari and M. Persiani, “Towards we-intentional human-robot interaction using theory of mind and hierarchical task network,” in 5th International Conference on Computer-Human Interaction Research and Applications (CHIRA), 2021.
[12] M. Persiani and T. Hellstr¨om, “Inference of the intentions of unknown agents in a theory of mind seing,” in Advances in Practical Applications of Agents, Multi-Agent Systems, and Social Good. The PAAMS Collection: 19th International Conference, Springer, 2021.
[13] M. Persiani and T. Hellstr¨om, “Probabilistic plan legibility with off-the-shelf planners,” in Workshop on Planning and Robotics (PlanRob @ICAPS), 2021.
[14] M. Persiani, “Computational models for intent recognition in robotic systems,” Licentiate Thesis. Department of Computing Science, Ume˚a University, 2020.
[15] M. Persiani and T. Hellstr¨om, “Intent recognition from speech and plan recognition,” in Advances in Practical Applications of Agents, Multi-Agent Systems, and Trustworthiness. The PAAMS Collection: 18th International Conference, pp. 212–223, Springer, 2020.
[16] M. Persiani, C. Odabasi, F. Graf, M. Kalra, T. Hellstroem, and B. Graf, “Traveling drinksman-a mobile service robot for people in care-homes,” in 52th International Symposium on Robotics (ISR), 2020.
[17] M. Tewari and M. Persiani, “Variational autoencoding dialogue sub-structures using a novel hierarchical annotation schema,” in 6th IEEE Congress on Information Science and Technology (CiSt), 2021.
[18] M. Persiani and M. Tewari, “Mediating joint intention with a dialogue management system,” in 1st International Workshop on New Foundations for Human-Centered AI (NeHuAI), 2020.
[19] M. Persiani and T. Hellstr¨om, “Unsupervised inference of object affordance from text corpora,” in 22nd Nordic Conference on Computational Linguistics (NoDaLiDa), 2019.
[20] M. Persiani, A. M. Franchi, and G. Gini, “A working memory model improves cognitive control in agents and robots,” Cognitive Systems Research, vol. 51, pp. 1–13, 2018.
[21] M. Persiani and T. Hellstr¨om, “Intent recognition for robotic applications,” in Workshop Robots in Contexts (@ECCE), 2017.
[22] M. Persiani, A. M. Franchi, and G. Gini, “From working memory to cognitive control: Presenting a model for their integration in a bio-inspired architecture,” Cognitive Robot Architectures, p. 67, 2017.
