Mark Law

513 citations
20 papers · 132 · h-index 7

Impact in

    • Logic, Reasoning, and Knowledge
    • Reinforcement Learning in Robotics
    • Topic Modeling
    • Privacy-Preserving Technologies in Data
    • Machine Learning and Algorithms
    • Multi-Agent Systems and Negotiation
    • AI-based Problem Solving and Planning

Papers in

    • Logic, Reasoning, and Knowledge 12
    • Multi-Agent Systems and Negotiation 8
    • Topic Modeling 5
    • Machine Learning and Algorithms 5
    • Natural Language Processing Techniques 3
    • Explainable Artificial Intelligence (XAI) 3
    • Adversarial Robustness in Machine Learning 2
    • Semantic Web and Ontologies 2

Mark Law

18 papers receiving 130 citations

Peers

Mark Law
Comparison fields: 5 of 36
  • Artificial Intelligence 106
  • Software 6
  • Computer Science Applications 5
  • Information Systems 19
  • Computer Networks and Communications 15
Replace Tomasz Lehmann with:
Tomasz Lehmann Poland
Piotr Nyczyk Switzerland
Ales Kubicek Switzerland
Nils Blach Switzerland
Adam Freeman United Kingdom
Roberta Răileanu United States
Felix Flentge Germany
Vegard Engen United Kingdom
Burcu Can Türkiye
Adelheit Stein Germany
Mark Law relative to Tomasz Lehmann Poland Tomasz Lehmann's profile →
Citations per field
00.5×1.5×
Tomasz Lehmann · 1×
Citations per year

Countries citing papers authored by Mark Law

Since Specialization
Citations

This map shows the geographic impact of Mark Law's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mark Law with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark Law more than expected).

Fields of papers citing papers by Mark Law

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mark Law. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mark Law. The network helps show where Mark Law may publish in the future.

Co-authors

The 25 scholars most cited alongside Mark Law, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Mark Law Line = papers co-authored together Mark Law links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 201822
2 201621
3 202020
4 201914
5 202012
6 201911
7 20029
8 20235
9 20213
10 20193
11 20213
12 20222
13 20212
14 20221
15
An Abductive-Inductive Algorithm for Probabilistic Inductive Logic Programming.
20161
16 20191
17
Machine Comprehension of Text Using Combinatory Categorial Grammar and Answer Set Programs.
20171
18 20191
19 20230
20 20190

About Mark Law

Mark Law is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Computer Networks and Communications, Sociology and Political Science and Statistical and Nonlinear Physics, having authored 20 papers that have together received 132 indexed citations. Recurring topics across this work include Logic, Reasoning, and Knowledge (12 papers), Multi-Agent Systems and Negotiation (8 papers), Topic Modeling (5 papers), Machine Learning and Algorithms (5 papers), Natural Language Processing Techniques (3 papers), Explainable Artificial Intelligence (XAI) (3 papers), Adversarial Robustness in Machine Learning (2 papers) and Semantic Web and Ontologies (2 papers). The work is most often cited by research in Artificial Intelligence (106 citations), Software (6 citations), Computer Science Applications (5 citations), Information Systems (19 citations) and Computer Networks and Communications (15 citations). Mark Law has collaborated with scholars based in United Kingdom, United States and Spain. Frequent co-authors include Alessandra Russo, Krysia Broda, Elisa Bertino, Jorge Lobo, Richard A. Abrams, Mark Levine, Avelie Stuart, Gül Çalıklı, Anders Jönsson and Seraphin Calo. Their work appears in journals such as Theory and Practice of Logic Programming, Machine Learning, Experimental Brain Research, Artificial Intelligence and Proceedings of the AAAI Conference on Artificial Intelligence.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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