Lawrence S. Moss

3.6k citations
84 papers · 1.0k indexed · h-index 16
Topics
Logic, Reasoning, and Knowledge (38 papers)Logic, programming, and type systems (29 papers)Semantic Web and Ontologies (16 papers)

In The Last Decade

Lawrence S. Moss

75 papers receiving 932 citations

Peers

Lawrence S. Moss
Comparison fields: 5 of 57
  • Artificial Intelligence 881
  • Computational Theory and Mathematics 492
  • Mathematical Physics 63
  • Computer Networks and Communications 51
  • Geometry and Topology 39
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Countries citing papers authored by Lawrence S. Moss

Since Specialization
Citations

This map shows the geographic impact of Lawrence S. Moss'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 Lawrence S. Moss with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lawrence S. Moss more than expected).

Fields of papers citing papers by Lawrence S. Moss

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lawrence S. Moss. 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 Lawrence S. Moss. The network helps show where Lawrence S. Moss may publish in the future.

Co-authorship network of co-authors of Lawrence S. Moss

This figure shows the co-authorship network connecting the top 25 collaborators of Lawrence S. Moss. A scholar is included among the top collaborators of Lawrence S. Moss based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Lawrence S. Moss. Lawrence S. Moss is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 16
2 38
3
Reasoning About the Sizes of Sets: Progress, Problems, and Prospects.
2
4 3
5 1
6
EQUATIONAL PROPERTIES OF RECURSIVE PROGRAM SCHEME SOLUTIONS
0
7 10
8 8
9
Advances in Modal Logic: Volume 9
3
10
Recursion Theorems and Self-Replication Via Text Register Machine Programs.
5
11 11
12 17
13 48
14
The logic of public announcements, common knowledge, and private suspicions
71
15 12
16 92
17 51
18 8
19 3
20 2

About Lawrence S. Moss

Lawrence S. Moss is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Theoretical Computer Science, having authored 84 papers that have together received 1.0k indexed citations. Recurring topics across this work include Logic, Reasoning, and Knowledge (38 papers), Logic, programming, and type systems (29 papers) and Semantic Web and Ontologies (16 papers). The work is most often cited by research in Computational Theory and Mathematics (492 citations), Artificial Intelligence (881 citations) and Mathematical Physics (63 citations). Lawrence S. Moss has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Alexandru Baltag, Rohit Parikh, Joseph S. Miller, Sławomir Solecki, Jonathan Ginzburg, Maarten de Rijke, Ian Pratt‐Hartmann, Stefan Milius, David E. Johnson and J. Michael Dunn. Their work appears in journals such as SHILAP Revista de lepidopterología, Theoretical Computer Science and Journal of Computer and System Sciences.

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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