Inductive Learning of Answer Set Programs. - Mark Law; Alessandra Russo; Krysia Broda (JELIA, 2014)

Automated Inference of Rules with Exception from Past Legal Cases Using ASP. - Duangtida Athakravi; Ken Satoh; Mark Law; Krysia Broda; Alessandra Russo (LPNMR, 2015)

Learning weak constraints in answer set programming. - Mark Law; Alessandra Russo; Krysia Broda (Theory Pract. Log. Program., 2015)

Privacy dynamics: learning privacy norms for social software. - Gül Çalikli; Mark Law; Arosha K. Bandara; Alessandra Russo; Luke Dickens; Blaine A. Price; Avelie Stuart; Mark Levine; Bashar Nuseibeh (SEAMS@ICSE, 2016)

An Abductive-Inductive Algorithm for Probabilistic Inductive Logic Programming. - Stanislav Dragiev; Alessandra Russo; Krysia Broda; Mark Law; Calin-Rares Turliuc (ILP (Short Papers), 2016)

Iterative Learning of Answer Set Programs from Context Dependent Examples. - Mark Law; Alessandra Russo; Krysia Broda (Theory Pract. Log. Program., 2016)

Machine Comprehension of Text Using Combinatory Categorial Grammar and Answer Set Programs. - Piotr Chabierski; Alessandra Russo; Mark Law; Krysia Broda (COMMONSENSE, 2017)

AGENP: An ASGrammar-based GENerative Policy Framework. - Seraphin B. Calo; Irene Manotas; Geeth de Mel; Daniel Cunnington; Mark Law; Dinesh C. Verma; Alessandra Russo; Elisa Bertino (PADG@ESORICS, 2018)

Learning Commonsense Knowledge Through Interactive Dialogue. - Benjamin Wu; Alessandra Russo; Mark Law; Katsumi Inoue (ICLP (Technical Communications), 2018)

The complexity and generality of learning answer set programs. - Mark Law; Alessandra Russo; Krysia Broda (Artif. Intell., 2018)

Inductive Learning of Answer Set Programs from Noisy Examples. - Mark Law; Alessandra Russo; Krysia Broda (CoRR, 2018)

Inductive learning of answer set programs. - Mark Law (2018)

Representing and Learning Grammars in Answer Set Programming. - Mark Law; Alessandra Russo; Elisa Bertino; Krysia Broda; Jorge Lobo 001 (AAAI, 2019)

Towards a Neural-Symbolic Generative Policy Model. - Daniel Cunnington; Mark Law; Alessandra Russo; Elisa Bertino; Seraphin B. Calo (IEEE BigData, 2019)

Generative Policies for Coalition Systems - A Symbolic Learning Framework. - Elisa Bertino; Graham White 002; Jorge Lobo 001; John Ingham; Gregory H. Cirincione; Alessandra Russo; Mark Law; Seraphin B. Calo; Irene Manotas; Dinesh C. Verma; Amani Abu Jabal; Daniel Cunnington; et al. (ICDCS, 2019)

A Comparison Between Statistical and Symbolic Learning Approaches for Generative Policy Models. - Graham White 002; Daniel Cunnington; Mark Law; Elisa Bertino; Geeth de Mel; Alessandra Russo (ICMLA, 2019)

A Generative Policy Model for Connected and Autonomous Vehicles. - Daniel Cunnington; Irene Manotas; Mark Law; Geeth de Mel; Seraphin B. Calo; Elisa Bertino; Alessandra Russo (ITSC, 2019)

A Demonstration of Generative Policy Models in Coalition Environments. - Daniel Cunnington; Graham White 002; Mark Law; Geeth de Mel (PAAMS, 2019)

Logic-Based Learning of Answer Set Programs. - Mark Law; Alessandra Russo; Krysia Broda (RW, 2019)

Using an ASG Based Generative Policy to Model Human Rules. - Graham White 002; John Ingham; Mark Law; Alessandra Russo (SMARTCOMP, 2019)

Induction of Subgoal Automata for Reinforcement Learning. - Daniel Furelos-Blanco; Mark Law; Alessandra Russo; Krysia Broda; Anders Jonsson 001 (AAAI, 2020)

FastLAS: Scalable Inductive Logic Programming Incorporating Domain-Specific Optimisation Criteria. - Mark Law; Alessandra Russo; Elisa Bertino; Krysia Broda; Jorge Lobo 001 (AAAI, 2020)

Polisma - A Framework for Learning Attribute-Based Access Control Policies. - Amani Abu Jabal; Elisa Bertino; Jorge Lobo 001; Mark Law; Alessandra Russo; Seraphin B. Calo; Dinesh C. Verma (ESORICS (1), 2020)

The ILASP system for Inductive Learning of Answer Set Programs. - Mark Law; Alessandra Russo; Krysia Broda (CoRR, 2020)

NSL: Hybrid Interpretable Learning From Noisy Raw Data. - Daniel Cunnington; Alessandra Russo; Mark Law; Jorge Lobo 001; Lance M. Kaplan (CoRR, 2020)

Inductive general game playing. - Andrew Cropper; Richard Evans 001; Mark Law (Mach. Learn., 2020)

Inductive Learning of Complex Knowledge from Raw Data. - Daniel Cunnington; Mark Law; Jorge Lobo 001; Alessandra Russo (TFSOCTAI@AAAI Fall Symposium, 2021)

Towards Neural-Symbolic Learning to support Human-Agent Operations. - Daniel Cunnington; Mark Law; Alessandra Russo; Jorge Lobo 001; Lance M. Kaplan (FUSION, 2021)

Scalable Non-observational Predicate Learning in ASP. - Mark Law; Alessandra Russo; Krysia Broda; Elisa Bertino (IJCAI, 2021)

Online Symbolic Learning of Policies for Explainable Security. - Arthur Drozdov; Mark Law; Jorge Lobo 001; Alessandra Russo; Mercion Wilathgamuwage Don (TPS-ISA, 2021)

FF-NSL: Feed-Forward Neural-Symbolic Learner. - Daniel Cunnington; Mark Law; Alessandra Russo; Jorge Lobo 001 (CoRR, 2021)

Induction and Exploitation of Subgoal Automata for Reinforcement Learning. - Daniel Furelos-Blanco; Mark Law; Anders Jonsson 001; Krysia Broda; Alessandra Russo (J. Artif. Intell. Res., 2021)

Search Space Expansion for Efficient Incremental Inductive Logic Programming from Streamed Data. - Mark Law; Krysia Broda; Alessandra Russo (IJCAI, 2022)

Learning to Rank the Distinctiveness of Behaviour in Serial Offending. - Mark Law; Théophile Sautory; Ludovico Mitchener; Kari Davies; Matthew Tonkin; Jessica Woodhams; Dalal Alrajeh (LPNMR, 2022)

Efficient Lifting of Symmetry Breaking Constraints for Complex Combinatorial Problems. - Alice Tarzariol; Konstantin Schekotihin; Martin Gebser; Mark Law (Theory Pract. Log. Program., 2022)

Learning to Break Symmetries for Efficient Optimization in Answer Set Programming. - Alice Tarzariol; Martin Gebser; Konstantin Schekotihin; Mark Law (AAAI, 2023)

Hierarchies of Reward Machines. - Daniel Furelos-Blanco; Mark Law; Anders Jonsson 001; Krysia Broda; Alessandra Russo (ICML, 2023)

Neuro-Symbolic Learning of Answer Set Programs from Raw Data. - Daniel Cunnington; Mark Law; Jorge Lobo 001; Alessandra Russo (IJCAI, 2023)

Towards ILP-Based LTL f Passive Learning. - Antonio Ielo; Mark Law; Valeria Fionda; Francesco Ricca; Giuseppe De Giacomo; Alessandra Russo (ILP, 2023)

A Unifying Framework for Learning Argumentation Semantics. - Zlatina Mileva; Antonis Bikakis; Fabio Aurelio D'Asaro; Mark Law; Alessandra Russo (CoRR, 2023)

FFNSL: Feed-Forward Neural-Symbolic Learner. - Daniel Cunnington; Mark Law; Jorge Lobo 001; Alessandra Russo (Mach. Learn., 2023)

Conflict-Driven Inductive Logic Programming. - Mark Law (Theory Pract. Log. Program., 2023)

Towards Explainable Weather Forecasting Through FastLAS. - Talissa Dreossi; Agostino Dovier; Andrea Formisano 001; Mark Law; Agostino Manzato; Alessandra Russo; Matthew Tait (LPNMR, 2024)

The Role of Foundation Models in Neuro-Symbolic Learning and Reasoning. - Daniel Cunnington; Mark Law; Jorge Lobo 001; Alessandra Russo (NeSy (1), 2024)