Andreas Niskanen

Education

• Doctor of Philosophy in Computer Science, November 2020
• PhD thesis: Computational Approaches to Dynamics and Uncertainty in Abstract Argumentation
• Master of Science in Computer Science, December 2016
• Master's thesis: Enforcement in Abstract Argumentation via Boolean Optimization
• Bachelor of Science in Mathematics, May 2016

Professional activities

• SPC member: IJCAI 2021
• PC member: KR 2024, ECAI 2024, IJCAI 2024, AAAI 2024, ECAI 2023, KR 2023, IJCAI 2023, AAAI 2023, KR 2022, IJCAI-ECAI 2022, AAAI 2022, AAAI 2021
• Reviewer: JAIR, AIJ, IJAR, AMAI

Publications

• Learning Big Logical Rules by Joining Small Rules. Céline Hocquette, Andreas Niskanen, Rolf Morel, Matti Järvisalo, and Andrew Cropper. Proceedings of the 33rd International Joint Conference on Artificial Intelligence (IJCAI 2024). To appear.
• Learning MDL Programs from Noisy Data. Céline Hocquette, Andreas Niskanen, Matti Järvisalo, and Andrew Cropper. Proceedings of 38th Annual AAAI Conference on Artificial Intelligence (AAAI 2024), pages 10553-10561. AAAI Press, 2024.
• MaxSAT-Based Inconsistency Measurement. Andreas Niskanen, Isabelle Kuhlmann, Matthias Thimm, and Matti Järvisalo. Proceedings of the 26th European Conference on Artificial Intelligence (ECAI 2023), volume 372 of Frontiers in Artificial Intelligence and Applications, pages 1779-1786. IOS Press, 2023.
• Computing MUS-Based Inconsistency Measures. Isabelle Kuhlmann, Andreas Niskanen, and Matti Järvisalo. Proceedings of the 18th European Conference on Logics in Artificial Intelligence (JELIA 2023), volume 14281 of Lecture Notes in Computer Science, pages 745-755. Springer, 2023.
• SAT-based Judgment Aggregation. Ari Conati, Andreas Niskanen, and Matti Järvisalo. Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2023), pages 1412-1420. ACM, 2023.
• Computing Smallest MUSes of Quantified Boolean Formulas. Andreas Niskanen, Jere Mustonen, Jeremias Berg, and Matti Järvisalo. Proceedings of the 16th International Conference on Logic Programming and Non-monotonic Reasoning (LPNMR 2022), volume 13416 of Lecture Notes in Computer Science, pages 301-314. Springer, 2022.[slides]
• Incremental Maximum Satisfiability. Andreas Niskanen, Jeremias Berg, and Matti Järvisalo. Proceedings of the 25th International Conference on Theory and Applications of Satisfiability Testing (SAT 2022), volume 236 of LIPIcs, pages 14:1-14:19. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022. [slides / SAT 2022] [slides / EURO 2022]
• MaxSAT-Based Bi-Objective Boolean Optimization. Christoph Jabs, Jeremias Berg, Andreas Niskanen, and Matti Järvisalo. Proceedings of the 25th International Conference on Theory and Applications of Satisfiability Testing (SAT 2022), volume 236 of LIPIcs, pages 12:1-12:23. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022.
• Advanced Algorithms for Abstract Dialectical Frameworks based on Complexity Analysis of Subclasses and SAT Solving. Thomas Linsbichler, Marco Maratea, Andreas Niskanen, Johannes P. Wallner, and Stefan Woltran. Artificial Intelligence, volume 307.
• Enabling Incrementality in the Implicit Hitting Set Approach to MaxSAT under Changing Weights. Andreas Niskanen, Jeremias Berg, and Matti Järvisalo. Proceedings of the 27th International Conference on Principles and Practice of Constraint Programming (CP 2021), pages 44:1-44:19, volume 210 of LIPIcs. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2021.
• Acceptance in Incomplete Argumentation Frameworks. Dorothea Baumeister, Matti Järvisalo, Daniel Neugebauer, Andreas Niskanen, Jörg Rothe. Artificial Intelligence, volume 295. [poster / IJCAI'21] [video / IJCAI'21]
• Smallest Explanations and Diagnoses of Rejection in Abstract Argumentation. Andreas Niskanen and Matti Järvisalo. Proceedings of the 17th International Conference on Principles of Knowledge Representation and Reasoning (KR 2020), pages 667-671. IJCAI, 2020. [slides]
• µ-toksia: An Efficient Abstract Argumentation Reasoner. Andreas Niskanen and Matti Järvisalo. Proceedings of the 17th International Conference on Principles of Knowledge Representation and Reasoning (KR 2020), pages 800-804. IJCAI, 2020. [slides]
• Controllability of Control Argumentation Frameworks. Andreas Niskanen, Daniel Neugebauer, and Matti Järvisalo. Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI-PRICAI 2020), pages 1855-1861. IJCAI, 2020. [poster] [video]
• Algorithms for Dynamic Argumentation Frameworks: An Incremental SAT-Based Approach. Andreas Niskanen and Matti Järvisalo. Proceedings of the 24th European Conference on Artificial Intelligence (ECAI 2020), pages 849-856, volume 325 of Frontiers in Artificial Intelligence and Applications. IOS Press, 2020. [slides]
• Strong Refinements for Hard Problems in Argumentation Dynamics. Andreas Niskanen and Matti Järvisalo. Proceedings of the 24th European Conference on Artificial Intelligence (ECAI 2020), pages 841-848, volume 325 of Frontiers in Artificial Intelligence and Applications. IOS Press, 2020. [slides]
• Deciding Acceptance in Incomplete Argumentation Frameworks. Andreas Niskanen, Daniel Neugebauer, Matti Järvisalo, and Jörg Rothe. Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI 2020), pages 2942-2949. AAAI Press, 2020. [poster] [slides]
• Synthesizing Argumentation Frameworks from Examples. Andreas Niskanen, Johannes P. Wallner, and Matti Järvisalo. Journal of Artificial Intelligence Research, volume 66, pages 503-554.
• Preprocessing Argumentation Frameworks via Replacement Patterns. Wolfgang Dvořák, Matti Järvisalo, Thomas Linsbichler, Andreas Niskanen, and Stefan Woltran. Proceedings of the 17th European Conference on Logics in Artificial Intelligence (JELIA 2019), volume 11468 of Lecture Notes in Computer Science, pages 116-132. Springer, 2019. [slides]
• Extension Enforcement under Grounded Semantics in Abstract Argumentation. Andreas Niskanen, Johannes P. Wallner, and Matti Järvisalo. Proceedings of the 16th International Conference on Principles of Knowledge Representation and Reasoning (KR 2018), pages 178-183. AAAI Press, 2018.
• SAT-based Approaches to Adjusting, Repairing, and Computing Largest Extensions of Argumentation Frameworks. Tuomo Lehtonen, Andreas Niskanen, and Matti Järvisalo. Proceedings of the 7th International Conference on Computational Models of Argument (COMMA 2018), pages 193-204, volume 305 of Frontiers in Artificial Intelligence and Applications. IOS Press, 2018.
• Novel Algorithms for Abstract Dialectical Frameworks based on Complexity Analysis of Subclasses and SAT Solving. Thomas Linsbichler, Marco Maratea, Andreas Niskanen, Johannes P. Wallner, and Stefan Woltran. Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI-ECAI 2018), pages 1905-1911. IJCAI, 2018. [poster] [slides]
• Complexity Results and Algorithms for Extension Enforcement in Abstract Argumentation. Johannes P. Wallner, Andreas Niskanen, and Matti Järvisalo. Journal of Artificial Intelligence Research, volume 60, pages 1-40.
• Pakota: A System for Enforcement in Abstract Argumentation. Andreas Niskanen, Johannes P. Wallner, and Matti Järvisalo. Proceedings of the 15th European Conference on Logics in Artificial Intelligence (JELIA 2016), volume 10021 of Lecture Notes in Computer Science, pages 385-400. Springer, 2016. [slides]
• Synthesizing Argumentation Frameworks from Examples. Andreas Niskanen, Johannes P. Wallner, and Matti Järvisalo. Proceedings of the 22nd European Conference on Artificial Intelligence (ECAI 2016), volume 285 of Frontiers in Artificial Intelligence and Applications, pages 551-559. IOS Press, 2016. [poster] [slides]
• Optimal Status Enforcement in Abstract Argumentation. Andreas Niskanen, Johannes P. Wallner, and Matti Järvisalo. Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI 2016), pages 1216-1222. AAAI Press, 2016.
• Complexity Results and Algorithms for Extension Enforcement in Abstract Argumentation. Johannes P. Wallner, Andreas Niskanen, and Matti Järvisalo. Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI 2016), pages 1088-1094. AAAI Press, 2016.

Software

Boolean optimization

• iMaxHS - Incremental MaxSAT solver.
• QBF-SMUSer - System for computing smallest MUSes of QBFs.

Computational argumentation

• µ-toksia - System for reasoning in standard and dynamic abstract argumentation frameworks.
  • ICCMA2019 version, static binary for Linux (64-bit): Download
• taeydennae - System for reasoning in incomplete argumentation frameworks.
• selitae - System for computing smallest explanations and diagnoses in abstract argumentation.
• pakota - System for enforcement in abstract argumentation.
• AFSynth - System for argumentation framework synthesis.
• k++ADF - System for reasoning in abstract dialectical frameworks.
• joukko - System for reasoning in argumentation frameworks with collective attacks.
• vaeite - System for reasoning in claim-augmented argumentation frameworks.

Computational social choice

• SATcha - System for judgment and preference aggregation.

Inconsistency measurement

• SAT4IM - System for inconsistency measurement.