Andy M. Tyrrell

4.1k citations
215 papers · 2.1k · h-index 23

Impact in

Papers in

    • Evolutionary Algorithms and Applications 85
    • Metaheuristic Optimization Algorithms Research 20
    • Reinforcement Learning in Robotics 17
    • Gene Regulatory Network Analysis 37

Andy M. Tyrrell

205 papers receiving 2.0k citations

Peers

Andy M. Tyrrell
Comparison fields: 5 of 122
  • Hardware and Architecture 218
  • Artificial Intelligence 875
  • Computational Theory and Mathematics 192
  • Electrical and Electronic Engineering 606
  • Cognitive Neuroscience 203
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Citations per field
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Citations per year

Countries citing papers authored by Andy M. Tyrrell

Since Specialization
Citations

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

Fields of papers citing papers by Andy M. Tyrrell

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Andy M. Tyrrell. 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 Andy M. Tyrrell. The network helps show where Andy M. Tyrrell may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 215 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200274
2 201172
3 202268
4 199460
5
Conceptual Frameworks for Artificial Immune Systems
200549
6 200248
7 201147
8 200543
9 201342
10 201737
11 201836
12 200235
13 200735
14 200232
15 200429
16 200028
17 200827
18 202326
19 201326
20 200225

About Andy M. Tyrrell

Andy M. Tyrrell is a scholar working on Artificial Intelligence, Molecular Biology, Electrical and Electronic Engineering, Mechanical Engineering and Biomedical Engineering, having authored 215 papers that have together received 2.1k indexed citations. Recurring topics across this work include Evolutionary Algorithms and Applications (85 papers), Gene Regulatory Network Analysis (37 papers), Modular Robots and Swarm Intelligence (35 papers), Advanced Memory and Neural Computing (25 papers), Metaheuristic Optimization Algorithms Research (20 papers), VLSI and FPGA Design Techniques (18 papers), Reinforcement Learning in Robotics (17 papers) and Neural dynamics and brain function (16 papers). The work is most often cited by research in Hardware and Architecture (218 citations), Artificial Intelligence (875 citations), Computational Theory and Mathematics (192 citations), Electrical and Electronic Engineering (606 citations) and Cognitive Neuroscience (203 citations). Andy M. Tyrrell has collaborated with scholars based in United Kingdom, Netherlands and United States. Frequent co-authors include Jon Timmis, Stephen L. Smith, Mahmoud Dhimish, Michael A. Lones, Martin A. Trefzer, James Alfred Walker, James A. Hilder, Pauline C. Haddow, Julian F. Miller and David M. Halliday. Their work appears in journals such as Biosystems, IEEE Transactions on Evolutionary Computation, Genetic Programming and Evolvable Machines, Robotics and IEEE Transactions on Neural Networks and Learning Systems.

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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