John Agapiou
Impact in
- Artificial Intelligence top 1%
- Reinforcement Learning in Robotics
- Topic Modeling
- Neural Networks and Applications
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- Multimodal Machine Learning Applications
Papers in
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- Advanced Measurement and Metrology Techniques 4
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- Reinforcement Learning in Robotics 5
- Evolutionary Algorithms and Applications 2
- Co-authors
- David A. Stephenson (1 shared paper)Joel Z. Leibo (5 shared papers)Audrūnas Gruslys (3 shared papers)Tom Schaul (3 shared papers)Todd Hester (3 shared papers)Olivier Pietquin (3 shared papers)Marc Lanctot (3 shared papers)Ian Osband (3 shared papers)
- Journals
- CIRP Annals (2 papers)Manufacturing Letters (1 paper)Journal of Neuroscience (1 paper)Nature (1 paper)Journal of Quality Technology (1 paper)
- Partner nations
- United StatesUnited KingdomAustralia
In The Last Decade
John Agapiou
21 papers receiving 1.7k citations
John Agapiou's Hit Papers
Peers
Comparison fields: 5 of 130
- Artificial Intelligence 901
- Computer Vision and Pattern Recognition 292
- Control and Systems Engineering 274
- Industrial and Manufacturing Engineering 91
- Automotive Engineering 103
Countries citing papers authored by John Agapiou
This map shows the geographic impact of John Agapiou'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 Agapiou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Agapiou more than expected).
Fields of papers citing papers by John Agapiou
This network shows the impact of papers produced by John Agapiou. 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 Agapiou. The network helps show where John Agapiou may publish in the future.
Co-authors
The 25 scholars most cited alongside John Agapiou, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Hybrid computing using a neural network with dynamic external memory Hit paper breakdown → | 2016 | 699 |
| 2 | Deep Q-learning From Demonstrations Hit paper breakdown → | 2018 | 493 |
| 3 | 2016 | 132 | |
| 4 | 2017 | 124 | |
| 5 | 2000 | 66 | |
| 6 | Learning from Demonstrations for Real World Reinforcement Learning | 2017 | 44 |
| 7 | 1995 | 37 | |
| 8 | 2009 | 25 | |
| 9 | Strategic Attentive Writer for Learning Macro-Actions | 2016 | 17 |
| 10 | 2021 | 16 | |
| 11 | 2009 | 16 | |
| 12 | 2008 | 14 | |
| 13 | 2019 | 12 | |
| 14 | 2019 | 10 | |
| 15 | 2023 | 9 | |
| 16 | 2019 | 9 | |
| 17 | 2012 | 8 | |
| 18 | 2017 | 3 | |
| 19 | 2022 | 1 | |
| 20 | 2024 | 1 |
About John Agapiou
John Agapiou is a scholar working on Mechanical Engineering, Artificial Intelligence, Electrical and Electronic Engineering, Electronic, Optical and Magnetic Materials and Industrial and Manufacturing Engineering, having authored 22 papers that have together received 1.7k indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (5 papers), Magnetic Properties and Applications (5 papers), Electric Motor Design and Analysis (4 papers), Advanced Measurement and Metrology Techniques (4 papers), Industrial Vision Systems and Defect Detection (3 papers), Metallurgy and Material Forming (2 papers), Evolutionary Algorithms and Applications (2 papers) and Manufacturing Process and Optimization (2 papers). The work is most often cited by research in Artificial Intelligence (901 citations), Computer Vision and Pattern Recognition (292 citations), Control and Systems Engineering (274 citations), Industrial and Manufacturing Engineering (91 citations) and Automotive Engineering (103 citations). John Agapiou has collaborated with scholars based in United States, United Kingdom and Australia. Frequent co-authors include David A. Stephenson, Joel Z. Leibo, Audrūnas Gruslys, Tom Schaul, Todd Hester, Olivier Pietquin, Marc Lanctot, Ian Osband, Gabriel Dulac-Arnold and Bilal Piot. Their work appears in journals such as CIRP Annals, Manufacturing Letters, Journal of Neuroscience, Nature and Journal of Quality Technology.
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.