Patrick Mannion

1.4k total citations · 1 hit paper
34 papers, 507 citations indexed

About

Patrick Mannion is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Management Science and Operations Research. According to data from OpenAlex, Patrick Mannion has authored 34 papers receiving a total of 507 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 10 papers in Computational Theory and Mathematics and 8 papers in Management Science and Operations Research. Recurrent topics in Patrick Mannion's work include Reinforcement Learning in Robotics (14 papers), Advanced Multi-Objective Optimization Algorithms (9 papers) and Auction Theory and Applications (6 papers). Patrick Mannion is often cited by papers focused on Reinforcement Learning in Robotics (14 papers), Advanced Multi-Objective Optimization Algorithms (9 papers) and Auction Theory and Applications (6 papers). Patrick Mannion collaborates with scholars based in Ireland, Belgium and United States. Patrick Mannion's co-authors include Enda Howley, Diederik M. Roijers, Roxana Rădulescu, Jim Duggan, Ann Nowé, Sam Devlin, Karl Mason, Conor F. Hayes, Mathieu Reymond and Fredrik Heintz and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and Neurocomputing.

In The Last Decade

Patrick Mannion

28 papers receiving 483 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
Patrick Mannion Ireland 11 194 98 85 84 70 34 507
Samrat Mondal India 14 224 1.2× 55 0.6× 75 0.9× 178 2.1× 73 1.0× 80 589
Roxana Rădulescu Belgium 7 114 0.6× 60 0.6× 41 0.5× 50 0.6× 46 0.7× 25 331
Tuncay Yi̇ği̇t Türkiye 11 164 0.8× 40 0.4× 148 1.7× 161 1.9× 46 0.7× 60 636
Adam Berry Australia 10 258 1.3× 98 1.0× 153 1.8× 286 3.4× 45 0.6× 30 647
Xiaowei Chen China 10 142 0.7× 64 0.7× 38 0.4× 68 0.8× 19 0.3× 40 662
Juana L. Redondo Spain 17 200 1.0× 105 1.1× 96 1.1× 149 1.8× 19 0.3× 71 782
Roberto Carballedo Spain 12 242 1.2× 83 0.8× 44 0.5× 41 0.5× 21 0.3× 25 457
Şener Akpınar Türkiye 11 205 1.1× 105 1.1× 33 0.4× 30 0.4× 66 0.9× 23 758
Ting-Cheng Chang China 10 93 0.5× 52 0.5× 38 0.4× 103 1.2× 103 1.5× 58 512
Syibrah Naim Malaysia 16 269 1.4× 33 0.3× 168 2.0× 222 2.6× 46 0.7× 33 636

Countries citing papers authored by Patrick Mannion

Since Specialization
Citations

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

Fields of papers citing papers by Patrick Mannion

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Patrick Mannion

This figure shows the co-authorship network connecting the top 25 collaborators of Patrick Mannion. A scholar is included among the top collaborators of Patrick Mannion 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 Patrick Mannion. Patrick Mannion 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.
Mason, Karl, et al.. (2025). Extending Evolution-Guided Policy Gradient Learning into the multi-objective domain. Neurocomputing. 636. 129991–129991.
2.
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
4.
Hayes, Conor F., et al.. (2023). Distributional Multi-Objective Decision Making. 5711–5719. 1 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.
Mannion, Patrick, et al.. (2022). A multi‐objective multi‐agent deep reinforcement learning approach to residential appliance scheduling. IET Smart Grid. 5(4). 260–280. 20 indexed citations
7.
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
8.
Mannion, Patrick, et al.. (2021). Tunable Behaviours in Sequential Social Dilemmas using Multi-Objective Reinforcement Learning. Autonomous Agents and Multi-Agent Systems. 1610–1612. 2 indexed citations
9.
Liontas, John I. & Patrick Mannion. (2021). Voices Heard, Voices Seen: From Classroom Praxis to Digital Stories Worth Sharing. SHILAP Revista de lepidopterología. 2 indexed citations
10.
Hayes, Conor F., Mathieu Reymond, Diederik M. Roijers, Enda Howley, & Patrick Mannion. (2021). Distributional Monte Carlo Tree Search for Risk-Aware and Multi-Objective Reinforcement Learning. VUBIR (Vrije Universiteit Brussel). 1530–1532. 7 indexed citations
11.
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
12.
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
13.
Li, Zhengjie, et al.. (2019). Future Teacher Educators in Critical Evaluation of Educational Technology through Collaborative Digital Storytelling Projects. Society for Information Technology & Teacher Education International Conference. 595–600. 1 indexed citations
14.
Mannion, Patrick, Sam Devlin, Jim Duggan, & Enda Howley. (2018). Reward shaping for knowledge-based multi-objective multi-agent reinforcement learning. The Knowledge Engineering Review. 33. 36 indexed citations
15.
Mannion, Patrick, et al.. (2018). Technology-Enhanced L2 Writing: A Systematic Literature Review and Analysis/Synthesis. 4(1). 127–150. 2 indexed citations
16.
Mannion, Patrick, Sam Devlin, Karl Mason, Jim Duggan, & Enda Howley. (2017). Policy invariance under reward transformations for multi-objective reinforcement learning. Neurocomputing. 263. 60–73. 27 indexed citations
17.
Mannion, Patrick, Jim Duggan, & Enda Howley. (2017). A Theoretical and Empirical Analysis of Reward Transformations in Multi-Objective Stochastic Games. Adaptive Agents and Multi-Agents Systems. 1625–1627. 6 indexed citations
18.
Mannion, Patrick, Sam Devlin, Jim Duggan, & Enda Howley. (2017). Multi-agent credit assignment in stochastic resource management games. The Knowledge Engineering Review. 32. 5 indexed citations
19.
Mannion, Patrick, Karl Mason, Sam Devlin, Jim Duggan, & Enda Howley. (2016). Multi-Objective Dynamic Dispatch Optimisation using Multi-Agent Reinforcement Learning: (Extended Abstract). Adaptive Agents and Multi-Agents Systems. 1345–1346. 14 indexed citations
20.
Mannion, Patrick. (1999). MOSFETs Break Out Of The Shackles Of Wirebonding.. 47(6). 42. 21 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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