John Levine

1.8k citations
78 papers · 1.2k · h-index 20

Impact in

Papers in

John Levine

64 papers receiving 1.1k citations

Peers

John Levine
Comparison fields: 5 of 102
  • Artificial Intelligence 700
  • Hardware and Architecture 131
  • Computer Networks and Communications 427
  • Software 65
  • Information Systems 303
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Citations per field
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Citations per year

Countries citing papers authored by John Levine

Since Specialization
Citations

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

Fields of papers citing papers by John Levine

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John Levine. 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 John Levine. The network helps show where John Levine may publish in the future.

Co-authors

The 25 scholars most cited alongside John Levine, 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 John Levine Line = papers co-authored together John Levine links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 78 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004130
2
A hybrid ant algorithm for scheduling independent jobs in heterogeneous computing environments
200488
3
A fast, effective local search for scheduling independent jobs in heterogeneous computing environments
200388
4 199569
5 201360
6 201355
7
Learning macro-actions for arbitrary planners and domains
200749
8 199239
9 201035
10
Lex and Yacc
199032
11
Experiences with Greylisting.
200530
12
Generation of multiple qualitatively different plan options
199830
13 201028
14
Graphics File Formats
199427
15 200426
16
AI-based game design patterns
201526
17
Using AI Planning Technology for Army small unit operations
200024
18 200122
19
Lex & yacc, 2nd edition
199221
20
flex & bison
200920

About John Levine

John Levine is a scholar working on Artificial Intelligence, Computer Networks and Communications, Information Systems, Electrical and Electronic Engineering and Clinical Psychology, having authored 78 papers that have together received 1.2k indexed citations. Recurring topics across this work include AI-based Problem Solving and Planning (11 papers), Artificial Intelligence in Games (10 papers), Reinforcement Learning in Robotics (8 papers), Evolutionary Algorithms and Applications (6 papers), Service-Oriented Architecture and Web Services (5 papers), Semantic Web and Ontologies (5 papers), Natural Language Processing Techniques (4 papers) and Psychological Testing and Assessment (4 papers). The work is most often cited by research in Artificial Intelligence (700 citations), Hardware and Architecture (131 citations), Computer Networks and Communications (427 citations), Software (65 citations) and Information Systems (303 citations). John Levine has collaborated with scholars based in United Kingdom, Chile and United States. Frequent co-authors include Graéme Ritchie, Chris Mellish, Ehud Reiter, Austin Tate, Jeff Dalton, Wenke Lee, Tommy Thompson, Xinzhou Qin, David Dagon and Guofei Gu. Their work appears in journals such as Journal of Personality Assessment, ACM SIGPLAN Notices, Duke Mathematical Journal, Theoretical Computer Science and Journal of Non-Crystalline Solids.

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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