I. Grondman

1.3k citations
8 papers · 841 indexed · 1 hit paper · h-index 6
Topics
Reinforcement Learning in Robotics (8 papers)Adaptive Dynamic Programming Control (6 papers)Advanced Control Systems Optimization (3 papers)
Journals
IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)MechatronicsIEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews)
Partner nations
NetherlandsRomaniaFrance

In The Last Decade

I. Grondman

8 papers receiving 802 citations

Hit Papers

A Survey of Actor-Critic Reinforcement Learning: Standard...20122026201620212012200400600

Peers

I. Grondman
Comparison fields: 5 of 86
  • Artificial Intelligence 349
  • Control and Systems Engineering 269
  • Electrical and Electronic Engineering 203
  • Computational Theory and Mathematics 186
  • Computer Networks and Communications 170
Replace Alexandra-Iulia Szedlak-Stinean with:
Alexandra-Iulia Szedlak-Stinean Romania
Claudiu Pozna Romania
Gabriel Dulac-Arnold United Kingdom
Jacopo Panerati Canada
Nantas Nardelli United Kingdom
Gregory Farquhar United Kingdom
Yiying Zhang China
Peter Vrancx Belgium
Samuel Coogan United States
Adam Gleave United Kingdom
I. Grondman relative to Alexandra-Iulia Szedlak-Stinean Romania Alexandra-Iulia Szedlak-Stinean's profile →
Citations per field
00.5×1.5×2.0×
Alexandra-Iulia Szedlak-Stinean · 1×
Citations per year

Countries citing papers authored by I. Grondman

Since Specialization
Citations

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

Fields of papers citing papers by I. Grondman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of I. Grondman

This figure shows the co-authorship network connecting the top 25 collaborators of I. Grondman. A scholar is included among the top collaborators of I. Grondman 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 I. Grondman. I. Grondman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

8 of 8 papers shown
#WorkIndexed citations
1 13
2 8
3 17
4 4
5 5
6
A Survey of Actor-Critic Reinforcement Learning: Standard and Natural Policy Gradientsbreakdown →
689
7 94
8 11

About I. Grondman

I. Grondman is a scholar working on Computational Theory and Mathematics, Control and Systems Engineering and Artificial Intelligence, having authored 8 papers that have together received 841 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (8 papers), Adaptive Dynamic Programming Control (6 papers) and Advanced Control Systems Optimization (3 papers). The work is most often cited by research in Computational Theory and Mathematics (186 citations), Control and Systems Engineering (269 citations) and Artificial Intelligence (349 citations). I. Grondman has collaborated with scholars based in Netherlands, Romania and France. Frequent co-authors include Robert Babuška, Lucian Buşoniu, Gabriel A. D. Lopes, Gregory Pinte, S. Jagannathan and Hao Xu. Their work appears in journals such as IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics), Mechatronics and IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews).

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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