Roxana Rădulescu

674 total citations · 1 hit paper
25 papers, 331 citations indexed

About

Roxana Rădulescu is a scholar working on Artificial Intelligence, Management Science and Operations Research and Economics and Econometrics. According to data from OpenAlex, Roxana Rădulescu has authored 25 papers receiving a total of 331 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 9 papers in Management Science and Operations Research and 6 papers in Economics and Econometrics. Recurrent topics in Roxana Rădulescu's work include Reinforcement Learning in Robotics (6 papers), Game Theory and Applications (5 papers) and Auction Theory and Applications (5 papers). Roxana Rădulescu is often cited by papers focused on Reinforcement Learning in Robotics (6 papers), Game Theory and Applications (5 papers) and Auction Theory and Applications (5 papers). Roxana Rădulescu collaborates with scholars based in Belgium, Netherlands and Ireland. Roxana Rădulescu's co-authors include Ann Nowé, Diederik M. Roijers, Patrick Mannion, Gabriel de Oliveira Ramos, Conor F. Hayes, Mathieu Reymond, Fredrik Heintz, Johan Källström, Peter Vamplew and Richard Dazeley and has published in prestigious journals such as Expert Systems with Applications, Renewable Energy and Artificial Intelligence.

In The Last Decade

Roxana Rădulescu

23 papers receiving 313 citations

Hit Papers

A practical guide to multi-objective reinforcement learni... 2022 2026 2023 2024 2022 50 100 150

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Roxana Rădulescu Belgium 7 114 60 50 49 46 25 331
Patrick Mannion Ireland 11 194 1.7× 98 1.6× 84 1.7× 63 1.3× 70 1.5× 34 507
Athirai A. Irissappane Singapore 9 169 1.5× 32 0.5× 35 0.7× 133 2.7× 41 0.9× 23 389
Péter Földesi Hungary 9 97 0.9× 31 0.5× 17 0.3× 22 0.4× 35 0.8× 54 272
Samir Aknine France 8 104 0.9× 17 0.3× 20 0.4× 95 1.9× 73 1.6× 49 305
Michela Fazzolari Italy 9 347 3.0× 56 0.9× 69 1.4× 38 0.8× 39 0.8× 20 529
Kaiyu Wan China 11 70 0.6× 18 0.3× 57 1.1× 138 2.8× 20 0.4× 46 331
Abdulqader M. Mohsen Yemen 9 228 2.0× 47 0.8× 49 1.0× 72 1.5× 11 0.2× 23 461
Flávio Vinícius Cruzeiro Martins Brazil 9 60 0.5× 71 1.2× 108 2.2× 98 2.0× 38 0.8× 30 274

Countries citing papers authored by Roxana Rădulescu

Since Specialization
Citations

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

Fields of papers citing papers by Roxana Rădulescu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Roxana Rădulescu

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

All Works

20 of 20 papers shown
1.
Rădulescu, Roxana, et al.. (2025). Multi-objective reinforcement learning for provably incentivising alignment with value systems. Artificial Intelligence. 351. 104460–104460.
2.
Grossi, Davide, et al.. (2025). Learning in public goods games: the effects of uncertainty and communication on cooperation. Neural Computing and Applications. 37(23). 18899–18932. 1 indexed citations
3.
Rădulescu, Roxana, et al.. (2025). Explainable AI Based Diagnosis of Poisoning Attacks in Evolutionary Swarms. Proceedings of the Genetic and Evolutionary Computation Conference Companion. 251–254. 1 indexed citations
4.
Reymond, Mathieu, Conor F. Hayes, Lander Willem, et al.. (2024). Exploring the Pareto front of multi-objective COVID-19 mitigation policies using reinforcement learning. Expert Systems with Applications. 249. 123686–123686. 4 indexed citations
5.
Hayes, Conor F., Roxana Rădulescu, Eugenio Bargiacchi, et al.. (2022). A practical guide to multi-objective reinforcement learning and planning. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 158 indexed citations breakdown →
6.
Vamplew, Peter, Benjamin J. Smith, Johan Källström, et al.. (2022). Scalar reward is not enough: a response to Silver, Singh, Precup and Sutton (2021). Autonomous Agents and Multi-Agent Systems. 36(2). 18 indexed citations
7.
Roijers, Diederik M., et al.. (2021). On Nash Equilibria for Multi-Objective Normal Form Games under Scalarised Expected Returns versus Expected Scalarised Returns. VUBIR (Vrije Universiteit Brussel). 1 indexed citations
8.
Rădulescu, Roxana, et al.. (2021). Communication Strategies in Multi-Objective Normal-Form Games. VUBIR (Vrije Universiteit Brussel). 2 indexed citations
9.
Ramos, Gabriel de Oliveira, et al.. (2020). Toll-Based Learning for Minimising Congestion under Heterogeneous Preferences. VUBIR (Vrije Universiteit Brussel). 1098–1106. 7 indexed citations
10.
Zhang, Yijie, Roxana Rădulescu, Patrick Mannion, Diederik M. Roijers, & Ann Nowé. (2020). Opponent Modelling for Reinforcement Learning in Multi-Objective Normal Form Games. VUBIR (Vrije Universiteit Brussel). 2080–2082. 2 indexed citations
11.
Ramos, Gabriel de Oliveira, Bruno C. da Silva, Roxana Rădulescu, Ana L. C. Bazzan, & Ann Nowé. (2020). Toll-based reinforcement learning for efficient equilibria in route choice. The Knowledge Engineering Review. 35. 6 indexed citations
12.
Zhang, Yijie, Roxana Rădulescu, Patrick Mannion, Diederik M. Roijers, & Ann Nowé. (2020). Opponent Modelling using Policy Reconstruction for Multi-Objective Normal Form Games. VUBIR (Vrije Universiteit Brussel). 1 indexed citations
13.
Rădulescu, Roxana, Patrick Mannion, Diederik M. Roijers, & Ann Nowé. (2019). Multi-objective multi-agent decision making: a utility-based analysis and survey. Autonomous Agents and Multi-Agent Systems. 34(1). 72 indexed citations
14.
Rădulescu, Roxana, et al.. (2019). Training a Speech-to-Text Model for Dutch on the Corpus Gesproken Nederlands. VUBIR (Vrije Universiteit Brussel). 2 indexed citations
15.
Ramos, Gabriel de Oliveira, Roxana Rădulescu, & Ann Nowé. (2019). A Budged-Balanced Tolling Scheme for Efficient Equilibria under Heterogeneous Preferences. VUBIR (Vrije Universiteit Brussel). 3 indexed citations
16.
Ramos, Gabriel de Oliveira, Bruno Castro da Silva, Roxana Rădulescu, & Ana L. C. Bazzan. (2018). Learning System-Efficient Equilibria in Route Choice Using Tolls. VUBIR (Vrije Universiteit Brussel). 1–9. 4 indexed citations
17.
Mihaylov, Mihail, et al.. (2018). Comparing stakeholder incentives across state-of-the-art renewable support mechanisms. Renewable Energy. 131. 689–699. 17 indexed citations
18.
Rădulescu, Roxana, Peter Vrancx, & Ann Nowé. (2017). Analysing Congestion Problems in Multi-agent Reinforcement Learning. Adaptive Agents and Multi-Agents Systems. 1705–1707. 3 indexed citations
19.
Rădulescu, Roxana & Katrien Beuls. (2016). Modelling pronominal gender agreement in Dutch. Belgian Journal of Linguistics. 30. 219–250. 1 indexed citations
20.
Mihaylov, Mihail, et al.. (2016). Boosting the Renewable Energy Economy with NRGcoin. 11 indexed citations

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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