Michael T. Cox

3.2k citations
110 papers · 1.6k · h-index 20

Impact in

Papers in

    • AI-based Problem Solving and Planning 43
    • Logic, Reasoning, and Knowledge 22
    • Multi-Agent Systems and Negotiation 17
    • Semantic Web and Ontologies 14
    • Extraction and Separation Processes 16

Michael T. Cox

97 papers receiving 1.5k citations

Peers

Michael T. Cox
Comparison fields: 5 of 142
  • Artificial Intelligence 786
  • Water Science and Technology 237
  • Filtration and Separation 32
  • Software 49
  • Industrial and Manufacturing Engineering 109
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Citations per field
00.5×10×16.3×
Angelo Chianese · 1×
Citations per year

Countries citing papers authored by Michael T. Cox

Since Specialization
Citations

This map shows the geographic impact of Michael T. Cox'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 Michael T. Cox with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael T. Cox more than expected).

Fields of papers citing papers by Michael T. Cox

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael T. Cox. 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 Michael T. Cox. The network helps show where Michael T. Cox may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 110 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005342
2 2005129
3 2002105
4 199961
5 199956
6 200051
7
Rationale-based monitoring for planning in dynamic environments
199850
8 200749
9 200548
10 200535
11 197534
12 200833
13 198432
14 201432
15 199230
16
Rationale-supported mixed-initiative case-based planning
199725
17 200523
18 200120
19 197520
20 198819

About Michael T. Cox

Michael T. Cox is a scholar working on Artificial Intelligence, Mechanical Engineering, Inorganic Chemistry, Information Systems and Water Science and Technology, having authored 110 papers that have together received 1.6k indexed citations. Recurring topics across this work include AI-based Problem Solving and Planning (43 papers), Logic, Reasoning, and Knowledge (22 papers), Multi-Agent Systems and Negotiation (17 papers), Extraction and Separation Processes (16 papers), Semantic Web and Ontologies (14 papers), Radioactive element chemistry and processing (10 papers), Adsorption and biosorption for pollutant removal (8 papers) and Chemical Synthesis and Characterization (6 papers). The work is most often cited by research in Artificial Intelligence (786 citations), Water Science and Technology (237 citations), Filtration and Separation (32 citations), Software (49 citations) and Industrial and Manufacturing Engineering (109 citations). Michael T. Cox has collaborated with scholars based in United States, United Kingdom and Spain. Frequent co-authors include Ashwin Ram, M. Aguilar, Mark T. Keane, El-Said I. El-Shafey, Ramón López de Mántaras, Derek Bridge, Barry Smyth, David McSherry, Boi Faltings and Agnar Aamodt. Their work appears in journals such as Solvent Extraction and Ion Exchange, Journal of Chemical Technology & Biotechnology, Hydrometallurgy, The Knowledge Engineering Review and The Journal of the Acoustical Society of America.

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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