Mark Law

Orcid: 0000-0003-4554-3415

According to our database1, Mark Law authored at least 43 papers between 2014 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Awards

IEEE Fellow

IEEE Fellow 1998, "For contributions to integrated circuits process modeling and simulation.".

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Other 

Links

On csauthors.net:

Bibliography

2024
The Role of Foundation Models in Neuro-Symbolic Learning and Reasoning.
CoRR, 2024

2023
Conflict-Driven Inductive Logic Programming.
Theory Pract. Log. Program., March, 2023

FFNSL: Feed-Forward Neural-Symbolic Learner.
Mach. Learn., February, 2023

A Unifying Framework for Learning Argumentation Semantics.
CoRR, 2023

Towards ILP-Based LTL f Passive Learning.
Proceedings of the Inductive Logic Programming - 32nd International Conference, 2023

Neuro-Symbolic Learning of Answer Set Programs from Raw Data.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Hierarchies of Reward Machines.
Proceedings of the International Conference on Machine Learning, 2023

Learning to Break Symmetries for Efficient Optimization in Answer Set Programming.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Efficient Lifting of Symmetry Breaking Constraints for Complex Combinatorial Problems.
Theory Pract. Log. Program., 2022

Learning to Rank the Distinctiveness of Behaviour in Serial Offending.
Proceedings of the Logic Programming and Nonmonotonic Reasoning, 2022

Search Space Expansion for Efficient Incremental Inductive Logic Programming from Streamed Data.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

2021
Induction and Exploitation of Subgoal Automata for Reinforcement Learning.
J. Artif. Intell. Res., 2021

FF-NSL: Feed-Forward Neural-Symbolic Learner.
CoRR, 2021

Online Symbolic Learning of Policies for Explainable Security.
Proceedings of the 3rd IEEE International Conference on Trust, 2021

Scalable Non-observational Predicate Learning in ASP.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Towards Neural-Symbolic Learning to support Human-Agent Operations.
Proceedings of the 24th IEEE International Conference on Information Fusion, 2021

Inductive Learning of Complex Knowledge from Raw Data.
Proceedings of the Thinking Fast and Slow and Other Cognitive Theories in AI, 2021

2020
Inductive general game playing.
Mach. Learn., 2020

NSL: Hybrid Interpretable Learning From Noisy Raw Data.
CoRR, 2020

The ILASP system for Inductive Learning of Answer Set Programs.
CoRR, 2020

Polisma - A Framework for Learning Attribute-Based Access Control Policies.
Proceedings of the Computer Security - ESORICS 2020, 2020

FastLAS: Scalable Inductive Logic Programming Incorporating Domain-Specific Optimisation Criteria.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Induction of Subgoal Automata for Reinforcement Learning.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Using an ASG Based Generative Policy to Model Human Rules.
Proceedings of the IEEE International Conference on Smart Computing, 2019

Logic-Based Learning of Answer Set Programs.
Proceedings of the Reasoning Web. Explainable Artificial Intelligence, 2019

A Demonstration of Generative Policy Models in Coalition Environments.
Proceedings of the Advances in Practical Applications of Survivable Agents and Multi-Agent Systems: The PAAMS Collection, 2019

A Generative Policy Model for Connected and Autonomous Vehicles.
Proceedings of the 2019 IEEE Intelligent Transportation Systems Conference, 2019

A Comparison Between Statistical and Symbolic Learning Approaches for Generative Policy Models.
Proceedings of the 18th IEEE International Conference On Machine Learning And Applications, 2019

Generative Policies for Coalition Systems - A Symbolic Learning Framework.
Proceedings of the 39th IEEE International Conference on Distributed Computing Systems, 2019

Towards a Neural-Symbolic Generative Policy Model.
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

Representing and Learning Grammars in Answer Set Programming.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Inductive learning of answer set programs.
PhD thesis, 2018

Inductive Learning of Answer Set Programs from Noisy Examples.
CoRR, 2018

The complexity and generality of learning answer set programs.
Artif. Intell., 2018

Learning Commonsense Knowledge Through Interactive Dialogue.
Proceedings of the Technical Communications of the 34th International Conference on Logic Programming, 2018

AGENP: An ASGrammar-based GENerative Policy Framework.
Proceedings of the Policy-Based Autonomic Data Governance [extended papers from the Second International Workshop on Policy-based Autonomic Data Governance, 2018

2017
Machine Comprehension of Text Using Combinatory Categorial Grammar and Answer Set Programs.
Proceedings of the Thirteenth International Symposium on Commonsense Reasoning, 2017

2016
Iterative Learning of Answer Set Programs from Context Dependent Examples.
Theory Pract. Log. Program., 2016

An Abductive-Inductive Algorithm for Probabilistic Inductive Logic Programming.
Proceedings of the 26th International Conference on Inductive Logic Programming (Short papers), 2016

Privacy dynamics: learning privacy norms for social software.
Proceedings of the 11th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, 2016

2015
Learning weak constraints in answer set programming.
Theory Pract. Log. Program., 2015

Automated Inference of Rules with Exception from Past Legal Cases Using ASP.
Proceedings of the Logic Programming and Nonmonotonic Reasoning, 2015

2014
Inductive Learning of Answer Set Programs.
Proceedings of the Logics in Artificial Intelligence - 14th European Conference, 2014


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