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2020 – today
- 2024
[c30]Talissa Dreossi
, Agostino Dovier, Andrea Formisano, Mark Law, Agostino Manzato, Alessandra Russo, Matthew Tait:
Towards Explainable Weather Forecasting Through FastLAS. LPNMR 2024: 262-275- [c29]Daniel Cunnington, Mark Law, Jorge Lobo, Alessandra Russo:
The Role of Foundation Models in Neuro-Symbolic Learning and Reasoning. NeSy (1) 2024: 84-100 - [i15]Daniel Cunnington, Mark Law, Jorge Lobo, Alessandra Russo:
The Role of Foundation Models in Neuro-Symbolic Learning and Reasoning. CoRR abs/2402.01889 (2024) - 2023
- [j8]Daniel Cunnington, Mark Law, Jorge Lobo, Alessandra Russo:
FFNSL: Feed-Forward Neural-Symbolic Learner. Mach. Learn. 112(2): 515-569 (2023) - [j7]Mark Law:
Conflict-Driven Inductive Logic Programming. Theory Pract. Log. Program. 23(2): 387-414 (2023) - [c28]Alice Tarzariol, Martin Gebser, Konstantin Schekotihin, Mark Law:
Learning to Break Symmetries for Efficient Optimization in Answer Set Programming. AAAI 2023: 6541-6549 - [c27]Daniel Furelos-Blanco, Mark Law, Anders Jonsson, Krysia Broda, Alessandra Russo:
Hierarchies of Reward Machines. ICML 2023: 10494-10541 - [c26]Daniel Cunnington, Mark Law, Jorge Lobo, Alessandra Russo:
Neuro-Symbolic Learning of Answer Set Programs from Raw Data. IJCAI 2023: 3586-3596 - [c25]Antonio Ielo, Mark Law, Valeria Fionda, Francesco Ricca, Giuseppe De Giacomo, Alessandra Russo:
Towards ILP-Based LTL f Passive Learning. ILP 2023: 30-45 - [i14]Zlatina Mileva, Antonis Bikakis, Fabio Aurelio D'Asaro, Mark Law, Alessandra Russo:
A Unifying Framework for Learning Argumentation Semantics. CoRR abs/2310.12309 (2023) - 2022
- [j6]Alice Tarzariol, Konstantin Schekotihin, Martin Gebser, Mark Law:
Efficient Lifting of Symmetry Breaking Constraints for Complex Combinatorial Problems. Theory Pract. Log. Program. 22(4): 606-622 (2022) - [c24]Mark Law, Krysia Broda, Alessandra Russo:
Search Space Expansion for Efficient Incremental Inductive Logic Programming from Streamed Data. IJCAI 2022: 2697-2704 - [c23]Mark Law, Théophile Sautory, Ludovico Mitchener, Kari Davies, Matthew Tonkin, Jessica Woodhams, Dalal Alrajeh:
Learning to Rank the Distinctiveness of Behaviour in Serial Offending. LPNMR 2022: 484-497 - [i13]Alice Tarzariol, Martin Gebser, Mark Law, Konstantin Schekotihin:
Efficient lifting of symmetry breaking constraints for complex combinatorial problems. CoRR abs/2205.07129 (2022) - [i12]Daniel Cunnington, Mark Law, Jorge Lobo, Alessandra Russo:
Inductive Learning of Complex Knowledge from Raw Data. CoRR abs/2205.12735 (2022) - [i11]Daniel Furelos-Blanco, Mark Law, Anders Jonsson, Krysia Broda, Alessandra Russo:
Hierarchies of Reward Machines. CoRR abs/2205.15752 (2022) - 2021
- [j5]Daniel Furelos-Blanco, Mark Law, Anders Jonsson, Krysia Broda, Alessandra Russo:
Induction and Exploitation of Subgoal Automata for Reinforcement Learning. J. Artif. Intell. Res. 70: 1031-1116 (2021) - [c22]Daniel Cunnington, Mark Law, Jorge Lobo, Alessandra Russo:
Inductive Learning of Complex Knowledge from Raw Data. TFSOCTAI@AAAI Fall Symposium 2021 - [c21]Daniel Cunnington, Mark Law, Alessandra Russo, Jorge Lobo, Lance M. Kaplan:
Towards Neural-Symbolic Learning to support Human-Agent Operations. FUSION 2021: 1-8 - [c20]Mark Law, Alessandra Russo, Krysia Broda, Elisa Bertino:
Scalable Non-observational Predicate Learning in ASP. IJCAI 2021: 1936-1943 - [c19]Arthur Drozdov, Mark Law, Jorge Lobo, Alessandra Russo, Mercion Wilathgamuwage Don:
Online Symbolic Learning of Policies for Explainable Security. TPS-ISA 2021: 269-278 - [i10]Mark Law:
Conflict-driven Inductive Logic Programming. CoRR abs/2101.00058 (2021) - [i9]Daniel Cunnington, Mark Law, Alessandra Russo, Jorge Lobo:
FF-NSL: Feed-Forward Neural-Symbolic Learner. CoRR abs/2106.13103 (2021) - 2020
- [j4]Andrew Cropper, Richard Evans, Mark Law:
Inductive general game playing. Mach. Learn. 109(7): 1393-1434 (2020) - [c18]Mark Law, Alessandra Russo, Elisa Bertino, Krysia Broda, Jorge Lobo:
FastLAS: Scalable Inductive Logic Programming Incorporating Domain-Specific Optimisation Criteria. AAAI 2020: 2877-2885 - [c17]Daniel Furelos-Blanco, Mark Law, Alessandra Russo, Krysia Broda, Anders Jonsson:
Induction of Subgoal Automata for Reinforcement Learning. AAAI 2020: 3890-3897 - [c16]Amani Abu Jabal, Elisa Bertino, Jorge Lobo, Mark Law, Alessandra Russo, Seraphin B. Calo, Dinesh C. Verma:
Polisma - A Framework for Learning Attribute-Based Access Control Policies. ESORICS (1) 2020: 523-544 - [i8]Mark Law, Alessandra Russo, Krysia Broda:
The ILASP system for Inductive Learning of Answer Set Programs. CoRR abs/2005.00904 (2020) - [i7]Daniel Furelos-Blanco, Mark Law, Anders Jonsson, Krysia Broda, Alessandra Russo:
Induction and Exploitation of Subgoal Automata for Reinforcement Learning. CoRR abs/2009.03855 (2020) - [i6]Daniel Cunnington, Alessandra Russo, Mark Law, Jorge Lobo, Lance M. Kaplan:
NSL: Hybrid Interpretable Learning From Noisy Raw Data. CoRR abs/2012.05023 (2020)
2010 – 2019
- 2019
- [c15]Mark Law, Alessandra Russo, Elisa Bertino, Krysia Broda, Jorge Lobo:
Representing and Learning Grammars in Answer Set Programming. AAAI 2019: 2919-2928 - [c14]Daniel Cunnington, Mark Law, Alessandra Russo, Elisa Bertino, Seraphin B. Calo:
Towards a Neural-Symbolic Generative Policy Model. IEEE BigData 2019: 4008-4016 - [c13]Elisa Bertino, Graham White, Jorge Lobo, John Ingham, Gregory H. Cirincione, Alessandra Russo, Mark Law, Seraphin B. Calo, Irene Manotas, Dinesh C. Verma, Amani Abu Jabal, Daniel Cunnington, Geeth de Mel:
Generative Policies for Coalition Systems - A Symbolic Learning Framework. ICDCS 2019: 1590-1600 - [c12]Graham White, Daniel Cunnington, Mark Law, Elisa Bertino, Geeth de Mel, Alessandra Russo:
A Comparison Between Statistical and Symbolic Learning Approaches for Generative Policy Models. ICMLA 2019: 1314-1321 - [c11]Daniel Cunnington, Irene Manotas, Mark Law, Geeth de Mel, Seraphin B. Calo, Elisa Bertino, Alessandra Russo:
A Generative Policy Model for Connected and Autonomous Vehicles. ITSC 2019: 1558-1565 - [c10]Daniel Cunnington, Graham White, Mark Law, Geeth de Mel:
A Demonstration of Generative Policy Models in Coalition Environments. PAAMS 2019: 242-245 - [c9]Mark Law, Alessandra Russo, Krysia Broda:
Logic-Based Learning of Answer Set Programs. RW 2019: 196-231 - [c8]Graham White, John Ingham, Mark Law, Alessandra Russo:
Using an ASG Based Generative Policy to Model Human Rules. SMARTCOMP 2019: 99-103 - [i5]Andrew Cropper, Richard Evans, Mark Law:
Inductive general game playing. CoRR abs/1906.09627 (2019) - [i4]Daniel Furelos-Blanco, Mark Law, Alessandra Russo, Krysia Broda, Anders Jonsson:
Induction of Subgoal Automata for Reinforcement Learning. CoRR abs/1911.13152 (2019) - 2018
- [b1]Mark Law:
Inductive learning of answer set programs. Imperial College London, UK, 2018 - [j3]Mark Law, Alessandra Russo, Krysia Broda:
The complexity and generality of learning answer set programs. Artif. Intell. 259: 110-146 (2018) - [c7]Seraphin B. Calo, Irene Manotas, Geeth de Mel, Daniel Cunnington, Mark Law, Dinesh C. Verma, Alessandra Russo, Elisa Bertino:
AGENP: An ASGrammar-based GENerative Policy Framework. PADG@ESORICS 2018: 3-20 - [c6]Benjamin Wu, Alessandra Russo, Mark Law, Katsumi Inoue:
Learning Commonsense Knowledge Through Interactive Dialogue. ICLP (Technical Communications) 2018: 12:1-12:19 - [i3]Mark Law, Alessandra Russo, Krysia Broda:
Inductive Learning of Answer Set Programs from Noisy Examples. CoRR abs/1808.08441 (2018) - 2017
- [c5]Piotr Chabierski, Alessandra Russo, Mark Law, Krysia Broda:
Machine Comprehension of Text Using Combinatory Categorial Grammar and Answer Set Programs. COMMONSENSE 2017 - 2016
- [j2]Mark Law, Alessandra Russo, Krysia Broda:
Iterative Learning of Answer Set Programs from Context Dependent Examples. Theory Pract. Log. Program. 16(5-6): 834-848 (2016) - [c4]Gül Çalikli, Mark Law, Arosha K. Bandara, Alessandra Russo, Luke Dickens, Blaine A. Price, Avelie Stuart, Mark Levine, Bashar Nuseibeh:
Privacy dynamics: learning privacy norms for social software. SEAMS@ICSE 2016: 47-56 - [c3]Stanislav Dragiev, Alessandra Russo, Krysia Broda, Mark Law, Calin-Rares Turliuc:
An Abductive-Inductive Algorithm for Probabilistic Inductive Logic Programming. ILP (Short Papers) 2016: 20-26 - [i2]Mark Law, Alessandra Russo, Krysia Broda:
Iterative Learning of Answer Set Programs from Context Dependent Examples. CoRR abs/1608.01946 (2016) - 2015
- [j1]Mark Law, Alessandra Russo, Krysia Broda:
Learning weak constraints in answer set programming. Theory Pract. Log. Program. 15(4-5): 511-525 (2015) - [c2]Duangtida Athakravi, Ken Satoh, Mark Law, Krysia Broda, Alessandra Russo:
Automated Inference of Rules with Exception from Past Legal Cases Using ASP. LPNMR 2015: 83-96 - [i1]Mark Law, Alessandra Russo, Krysia Broda:
Learning Weak Constraints in Answer Set Programming. CoRR abs/1507.06566 (2015) - 2014
- [c1]Mark Law, Alessandra Russo, Krysia Broda:
Inductive Learning of Answer Set Programs. JELIA 2014: 311-325
Coauthor Index
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