Marek Grześ
Impact in
- Artificial Intelligence top 5%
- Reinforcement Learning in Robotics
- Evolutionary Algorithms and Applications
- AI-based Problem Solving and Planning
- Metaheuristic Optimization Algorithms Research
- Machine Learning and Data Classification
- Neural Networks and Applications
Papers in
-
- Reinforcement Learning in Robotics 24
- Evolutionary Algorithms and Applications 17
- Machine Learning and Algorithms 7
- Machine Learning and Data Classification 3
- Topic Modeling 3
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- Formal Methods in Verification 5
- Co-authors
- Daniel Kudenko⋆ (15 shared papers)Marek Krętowski (12 shared papers)Sam Devlin (3 shared papers)Jesse Hoey (7 shared papers)Scott Sanner (1 shared paper)Mauro Vallati (1 shared paper)Marcin Czajkowski (2 shared papers)Mark Roberts (1 shared paper)
- Journals
- Neural Networks (3 papers)Neural Computation (2 papers)Lecture notes in computer science (11 papers)Artificial Intelligence in Medicine (1 paper)International Journal of Approximate Reasoning (1 paper)
- Partner nations
- United KingdomCanadaPoland
In The Last Decade
Marek Grześ
47 papers receiving 658 citations
Peers
Comparison fields: 5 of 79
- Artificial Intelligence 510
- Computational Theory and Mathematics 102
- Management Science and Operations Research 67
- Information Systems 108
- Software 15
Countries citing papers authored by Marek Grześ
This map shows the geographic impact of Marek Grześ'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 Marek Grześ with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marek Grześ more than expected).
Fields of papers citing papers by Marek Grześ
This network shows the impact of papers produced by Marek Grześ. 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 Marek Grześ. The network helps show where Marek Grześ may publish in the future.
Co-authors
The 23 scholars most cited alongside Marek Grześ, 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 51 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 79 | |
| 2 | 2011 | 57 | |
| 3 | 2008 | 55 | |
| 4 | 2017 | 47 | |
| 5 | 2010 | 47 | |
| 6 | 2014 | 36 | |
| 7 | 2019 | 33 | |
| 8 | 2005 | 28 | |
| 9 | 2007 | 26 | |
| 10 | 2009 | 22 | |
| 11 | 2006 | 20 | |
| 12 | 2008 | 19 | |
| 13 | 2006 | 17 | |
| 14 | 2020 | 15 | |
| 15 | Learning Shaping Rewards in Model-based Reinforcement Learning | 2009 | 15 |
| 16 | 2019 | 13 | |
| 17 | Isomorph-free branch and bound search for finite state controllers | 2013 | 12 |
| 18 | 2013 | 12 | |
| 19 | 2007 | 12 | |
| 20 | 2006 | 11 |
About Marek Grześ
Marek Grześ is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Information Systems, Management Science and Operations Research and Molecular Biology, having authored 51 papers that have together received 688 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (24 papers), Evolutionary Algorithms and Applications (17 papers), Data Mining Algorithms and Applications (8 papers), Machine Learning and Algorithms (7 papers), Formal Methods in Verification (5 papers), Simulation Techniques and Applications (4 papers), Machine Learning and Data Classification (3 papers) and Topic Modeling (3 papers). The work is most often cited by research in Artificial Intelligence (510 citations), Computational Theory and Mathematics (102 citations), Management Science and Operations Research (67 citations), Information Systems (108 citations) and Software (15 citations). Marek Grześ has collaborated with scholars based in United Kingdom, Canada and Poland. Frequent co-authors include Daniel Kudenko⋆, Marek Krętowski, Sam Devlin, Jesse Hoey, Scott Sanner, Mauro Vallati, Marcin Czajkowski, Mark Roberts, Lukáš Chrpa and T.L. McCluskey. Their work appears in journals such as Neural Networks, Neural Computation, Lecture notes in computer science, Artificial Intelligence in Medicine and International Journal of Approximate Reasoning.
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.