Five papers presented at AAAI 2020 and ten more papers accepted

34th AAAI Conference on Artificial Intelligence, New York City, US.

Five papers by members of the Department of Computing have been presented at the 34th AAAI Conference on Artificial Intelligence (AAAI20), 7-12 February 2020, New York City, US.

In addition, a total of ten papers by members of the Department have been accepted for presentation at the 19th International Conference on Autonomous Agents and Multiagent Systems (AAMAS2020), 9-13 May 2020, Auckland, New Zealand, and at the 24th European Conference on Artificial Intelligence (ECAI2020) 10-12 June 2020, Santiago de Compostela, Spain.

AAAI, AAMAS and ECAI are all premier conferences in AI. AAAI20 accepted 1,591 papers out of 7,737 reviewed papers, AAMAS2020 accepted 186 full papers out of 808 submissions, and ECAI2020 accepted 365 full papers out of 1363 reviewed ones.

The papers are:

*AAAI2020

1. Botoeva, Kouvaros, Kronqvist, Lomuscio, Misener: Efficient Verification of Neural Networks via Dependency Analysis.

2. Belardinelli, Lomuscio, Yu. Model Checking Temporal Epistemic Logic under Bounded Recall.
(This is based on the final year undergraduate project 2018-19 by Yu)

3. Bulat, Kossaifi, Tzimiropoulos, Pantic: Incremental multi-domain learning with network latent tensor factorization

4. Furelos-Blanco, Law, Russo, Broda, Jonsson: Induction of Subgoal Automata for Reinforcement Learning

5. Law, Russo, Bertino, Broda, Lobo: Scalable Inductive Logic Programming incorporating Domain-specific Optimisation Criteria

*AAMAS 2020:

1. Akitunde, Botoeva, Kouvaros, Lomuscio: Formal Verification of Neural Agents in Non-deterministic Environments.

2. Lomuscio, Pirovano: Parameterised Verification of Strategic Properties in Probabilistic Multi-Agent Systems.

3. Luo, Jennings: A budget-limited mechanism for category-aware crowdsourcing systems

4. Mahmud, Choudhury, Khan, Tran-Thanh, Jennings: AED: an anytime evolutionary DCOP algorithm

*ECAI 2020:

1. Belardinelli, Demri: Reasoning with a Bounded Number of Resources in ATL+

2. Belardinelli, Malvone: Verifying Strategic Abilities in Multi-agent Systems via First-order Entailment

3. Cocarascu, Stylianou, Cyras, Toni: Data-Empowered Argumentation for Dialectically Explainable Predictions

4. Henriksen, Lomuscio: Efficient Neural Network Verification via Adaptive Refinement and Adversarial Search.
(This is based on the MSc project 2018-19 by Henriksen)

5. Leon, Belardinelli: Extended Markov Games to Learn Multiple Tasks in Multi-Agent Reinforcement Learning

6. Scarton, Madhyastha, Specia: Deciding When, How and for Whom to Simplify