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Opponent modeling in a PGM framework.

, , и . AAMAS, стр. 1149-1150. IFAAMAS, (2013)

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Nicolaj Faigle

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Nicolaj Mahlstedt

Nicolaj Zarewskij

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A Software System for Predicting Patient Flow at the Emergency Department of Aalborg University Hospital., , , , , , , , и . PGM, том 138 из Proceedings of Machine Learning Research, стр. 617-620. PMLR, (2020)Acting under Interference by other Agents with unknown Goals., и . SCAI, том 173 из Frontiers in Artificial Intelligence and Applications, стр. 157-164. IOS Press, (2008)A PGM framework for recursive modeling of players in simple sequential Bayesian games., и . Int. J. Approx. Reason., 51 (5): 587-599 (2010)A component framework as an enabler for industrial cyber physical systems., , , , , , и . ICPS, стр. 339-344. IEEE, (2018)A methodology for developing local smart diagnostic models using expert knowledge., , , и . INDIN, стр. 1682-1687. IEEE, (2015)Prediction of High Risk of Deviations in Home Care Deliveries., , , , , , , и . PGM, том 138 из Proceedings of Machine Learning Research, стр. 281-292. PMLR, (2020)Opponent modeling in a PGM framework., , и . AAMAS, стр. 1149-1150. IFAAMAS, (2013)Parameter Learning Algorithms for Continuous Model Improvement Using Operational Data., , , , , , , и . ECSQARU, том 10369 из Lecture Notes in Computer Science, стр. 115-124. Springer, (2017)Applying Object-Oriented Bayesian Networks for Smart Diagnosis and Health Monitoring at both Component and Factory Level., , , , и . IEA/AIE (2), том 10351 из Lecture Notes in Computer Science, стр. 132-141. Springer, (2017)SelSus: Towards a reference architecture for diagnostics and predictive maintenance using smart manufacturing devices., , , и . INDIN, стр. 1700-1705. IEEE, (2015)