Accepted papers by TAILOR scientists to AAAI 2023

A lot of TAILOR scientists submitted their paperwork to the 37th AAAI Conference on Artificial Intelligence (AAAI 2023), which will take place in n Washington, DC, US from February 7th to 14th, 2023.

Here below is the (not full) list of accepted papers presented by people involved in TAILOR:

  • Giulio Rossolini, Federico Nesti, Fabio Brau, Alessandro Biondi, and Giorgio Buttazzo, “Defending From Physically-Realizable Adversarial Attacks Through Internal Over-Activation Analysis“.
  • Fabio Brau, Giulio Rossolini, Alessandro Biondi, and Giorgio Buttazzo, “Robust-by-Design Classification via Unitary-Gradient Neural Networks“.
  • Benjamin Aminof, Giuseppe De Giacomo, Sasha Rubin, “Reactive Synthesis of Dominant Strategies”.
  • Alessandro Ronca, Nadezda Alexandrovna Knorozova, Giuseppe De Giacomo, “Sample Complexity of Automata Cascades”.
  • Roberto Cipollone, Giuseppe De Giacomo, Marco Favorito, Luca Iocchi, Fabio Patrizi, “Exploiting Multiple Abstractions in Episodic RL via Reward Shaping“.
  • Thibault Gauthier, Josef Urban, “Learning Program Synthesis for Integer Sequences from Scratch
  • Anna Gautier, Nick Hawes, Bruno Lacerda, and Michael Wooldridge. Multi-Unit Auctions for Allocating Chance-Constrained Resources
  • Gianvincenzo Alfano, Sergio Greco, Francesco Parisi, Irina Trubitsyna, “Abstract Argumentation Frameworks with Conditional Preferences
  • Dimosthenis C. Tsouros, Tias Guns and Kostas Stergiou, “Learning constraint models from data
  • Maxime Mulamba Ke Tchomba, Emilio Gamba and Tias Guns, “Constraint solving for Prediction + Optimisation problems
  • (demonstration) Tias Guns, Emilio Gamba, Maxime Mulamba Ke Tchomba, Ignace Bleukx, Senne Berden and Milan Pesa, “Sudoku Assistant – An AI-powered app to help solve pen-and-paper Sudokus
  • Songtuan Lin, Gregor Behnke, Simona Ondrčková, Roman Barták, Pascal Bercher, “On Total-Order HTN Plan Verification with Method Preconditions — An Extension of the CYK Parsing Algorithm
  • Leonardo Lamanna, Luciano Serafini, Mohamadreza Faridghasemnia, Alessandro Saffiotti, Alessandro Saetti, Alfonso Gerevini, Paolo Traverso, “Planning for Learning Object Properties
  • Sarit Kraus, Yaniv Oshrat, Yonatan Aumann, Tal Hollander, Oleg Maksimov, Anita Ostroumov and Natali Shechtman, “Customer Service Combining Human Operators and Virtual Agents: a Call for Multidisciplinary AI Research“.
  • Yohai Trabelsi, Abhijin Adiga, Sarit Kraus, S.S. Ravi, Daniel J. Rosenkrantz, “Resource Sharing Through Multi-Round Matchings
  • Sarit Kraus B11: AI and Law
  • Michael Bernreiter, Wolfgang Dvorak, Anna Rapberger, Stefan Woltran, “The Effect of Preferences in Abstract Argumentation Under a Claim-Centric View
  • Markus Brill, Stefan Forster, Martin Lackner, Jan Maly and Jannik Peters, “Proportionality in Approval-Based Participatory Budgeting
  • Johannes Fichte, Markus Hecher, Stefan Szeider, “Inconsistent Cores for ASP: The Perks and Perils of Non-Monotonicity
  • Markus Hecher: Characterizing Structural Hardness of Logic Programs: “What makes Cycles and Reachability Hard for Treewidth?
  • Lucas Kletzander and Nysret Musliu, “Large-State Reinforcement Learning for Hyper-Heuristics
  • Martin Lackner and Jan Maly, “Proportional Decisions in Perpetual Voting
  • Franz-Xaver Reichl, Friedrich Slivovsky, Stefan Szeider, “Circuit Minimization with QBF-Based Exact Synthesis
  • G. Cima, M. Console, M. Lenzerini, A. Poggi, “Epistemic Disjunctive Datalog for Querying Knowledge Bases
  • Hasra Dodampegama and Mohan Sridharan, “Back to the Future: Toward a Hybrid Architecture for Ad Hoc Teamwork
  • Mohan Sridharan, “Integrated Knowledge-based and Data-driven Reasoning, Learning, and Collaboration in Robotics“. (Bridge Session on AI and Robotics)
  • Raphael Fischer, Matthias Jakobs, Katharina Morik, “Energy Efficiency Considerations for Popular AI Benchmarks
  • König, Bosman, Hoos, van Rijn, “Critically Assessing the State of the Art in CPU-based Local Robustness Verification
  • M. Fuccellaro, L. Simon, A. Zemmari, “A Robust Drift Detection Algorithm with High Accuracy and Low False Positives Rate
Find an overview of the AAAI Conference program here: