Matthias Thimm
Projects (Current)
  • MIB: Predictive and Interactive Management of Potential Inconsistencies in Business Rules (2024-, DFG Research Project)
  • AIM: Algorithms for Inconsistency Measurement (2023-, DFG Research Project)
  • EBM: Explainable Belief Merging (2022-, DFG Research Project)
  • CAML2: Causality, Argumentation, and Machine Learning (2021-, DFG Research Project)
  • EnTrust: Engineering Trustworthy Data-Intensive Systems (2019-, funded by Rhineland-Palatinate)
  • FAT IL: Foundations, Applications & Theory of Inductive Logic (2019-, DFG Scientific Network)
Projects (Past)
  • CAR: Conditional Argumentative Reasoning (2019-2022, DFG Research Project)
  • HIBPM: Handling Inconsistencies in Business Process Modelling (2019-2022, DFG Research Project)
  • CAML: Argumentative Machine Learning (2018-2021, DFG Research Project)
  • Live+Gov: Reality Sensing, Mining and Augmentation for Mobile Citizen-eGovernment Dialogue (2012-2015, funded by EU 7th Framework Programme)
  • SocialSensor: Sensing User Generated Input for Improved Media Discovery and Experience (2011-2014, funded by EU 7th Framework Programme)
  • KReate: Logic-based probabilistic knowledge representation for relational learning, modeling, and reasoning (2008-2011, funded by Deutsche Forschungsgemeinschaft)
  • PROALAR BR+ARG: Combining belief revision and argumentation for enhancing the reasoning capabilities of agents in multiagent system (2010-2011, funded by Deutscher Akademischer Auslandsdienst)
  • "Exchange and Fusion of Information under Availability and Confidentiality Requirements in Multi-Agent Systems" in the collaborative research center "SFB 876: Providing Information by Resource-Constrained Data Analysis", (2011-, funded by Deutsche Forschungsgemeinschaft)
  • TweetyProject: A comprehensive Java library for logic aspects of artificial intelligence and knowledge representation
  • AIG GitHub: Various implementations of AIG at GitHub
  • heureka: A heuristic backtracking solver for abstract argumentation
  • probo: A Benchmark Framework for Computational Argumentation Competitions
  • KReator: A toolbox for relational probabilistic knowledge representation, reasoning, and learning
© Matthias Thimm - Terms