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The Complex Event Recognition Group, one of the six research groups that are active within SKEL Lab, co-organised the RACES workshop (Reasoning about ACtions and Events over Streams). The workshop was held virtually, on Saturday 12 September, as part of the 17th International Conference on Principles of Knowledge Representation and Reasoning (KR2020, 12-18 September 2020), which is sister conference of the 11th Hellenic Conference on Artificial Intelligence (SETN) 2020.

Workshop Info and Goal
In order to obtain timely insights and implement reactive and proactive measures, many contemporary applications require reasoning about actions and events over streams of continuously arriving data. For example, in a wide range of applications, critical activities are formalised as events that have to be detected in real-time, or even forecast ahead of time. The workshop aimed to bring together researchers working in various areas, such as knowledge representation, machine learning, database systems, complexity theory, distributed systems and business process modeling, and thus foster community building on reasoning on actions and events over streams.


Accepted Papers

Presentations below are available to view here and via a playlist here.

  • Periklis Mantenoglou, Online Probabilistic Interval-based Event Calculus
  • Andrea Brunello, Dario Della Monica, Angelo Montanari and Andrea Urgolo, Learning to Monitor: a Novel Framework for Online System Verific
  • Efthimis Tsilionis, Incremental Event Calculus for Run-Time Reasoning
  • Przemysław Andrzej Walega, Bernardo Cuenca Grau and Egor V. Kostylev, Temporal Stream Reasoning with DatalogMTL
  • Thomas Prokosch and François Bry, Stream Reasoning Back and Forth
  • Franco Giustozzi, Julien Saunier and Cecilia Zanni-Merk, Abnormal Situations Interpretation in Industry 4.0 using Stream Reasoning
  • Alberto Camacho and Sheila A. McIlraith, Learning Interpretable Models Expressed in Linear Temporal Logic
  • Thomas Eiter and Rafael Kiesel, Quantities in Stream Reasoning
  • Pietro Daverio, Hassan Nazeer Chaudhry, Alessandro Margara and Matteo Rossi, Temporal Reasoning on Large-Scale Graphs
  • Patrik Schneider and Thomas Eiter, Temporal Behavioral Models for Traffic Diagnosis
  • Jean-Pierre Münch, Florian Weinacker, Guido Salvaneschi and Alessandro Margara, Accountable Decentralized Event Reasoning Using Blockchains


Invited Talk

Cristian Rivero, PUC Chile & Millenium Institute for Foundational Research on Data, was invited to give a talk entitled A theoretical approach for complex event recognition.


General overview of the recent proposal for a logic, computational model, and query evaluation techniques for complex event recognition. The speaker starts by presenting a logic for extracting complex events, called Complex Event Logic (CEL), which is given by a compositional and denotational semantics. He continues by introducing an automata model for declaring complex events that captures CEL’s expressive power, that is, every CEL formula can be compiled into such an automaton. Interestingly, by extending CEL with projection and strict sequencing, one can prove that both CEL and the automata model are equally expressive. Following is an algorithmic approach for evaluating this class of queries with strong guarantees of efficiency, namely, constant update time and constant-delay between outputs. The evaluation approach even holds for CEL formulas with partition-by, an operator usually used in CER systems for correlating events. These results are part of a joint work with Alejandro Grez, Stijn Vansummeren, and Martin Ugarte.

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