Lenz Belzner

1.1k total citations · 1 hit paper
29 papers, 620 citations indexed

About

Lenz Belzner is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Management Science and Operations Research. According to data from OpenAlex, Lenz Belzner has authored 29 papers receiving a total of 620 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Artificial Intelligence, 6 papers in Computational Theory and Mathematics and 6 papers in Management Science and Operations Research. Recurrent topics in Lenz Belzner's work include Reinforcement Learning in Robotics (12 papers), Evolutionary Algorithms and Applications (3 papers) and Computability, Logic, AI Algorithms (3 papers). Lenz Belzner is often cited by papers focused on Reinforcement Learning in Robotics (12 papers), Evolutionary Algorithms and Applications (3 papers) and Computability, Logic, AI Algorithms (3 papers). Lenz Belzner collaborates with scholars based in Germany, Romania and Spain. Lenz Belzner's co-authors include Thomas Altenmüller, Bernd Waschneck, Andreas Kyek, Alexander Knapp, André Reichstaller, Thomas Bauernhansl, Thomas Gabor, Michael Till Beck, Alexander Neitz and Thomy Phan and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Science of The Total Environment and Autonomous Agents and Multi-Agent Systems.

In The Last Decade

Lenz Belzner

25 papers receiving 596 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Optimization of global production scheduling with deep reinforcement learning

2018 264 citations Bernd Waschneck, André Reichstaller et al. Procedia CIRP profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Lenz Belzner Germany	7	444	112	89	72	37	29	620
Bernd Waschneck Germany	6	388 0.9×	71 0.6×	93 1.0×	43 0.6×	41 1.1×	16	514
Minghai Yuan China	14	579 1.3×	45 0.4×	74 0.8×	72 1.0×	19 0.5×	51	724
Jiapeng Yu China	9	307 0.7×	39 0.3×	62 0.7×	58 0.8×	65 1.8×	21	501
Appa Iyer Sivakumar Singapore	16	723 1.6×	160 1.4×	99 1.1×	126 1.8×	114 3.1×	52	901
François de Bertrand de Beuvron France	11	130 0.3×	116 1.0×	67 0.8×	23 0.3×	27 0.7×	34	372
Meimei Gao United States	7	182 0.4×	52 0.5×	53 0.6×	39 0.5×	72 1.9×	10	390
Judith Michael Germany	12	218 0.5×	160 1.4×	39 0.4×	68 0.9×	86 2.3×	62	502
Buyun Sheng China	11	200 0.5×	40 0.4×	39 0.4×	37 0.5×	21 0.6×	70	408
Jihui Zhang China	10	183 0.4×	85 0.8×	74 0.8×	47 0.7×	43 1.2×	35	413

Countries citing papers authored by Lenz Belzner

Since Specialization

Citations

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

Fields of papers citing papers by Lenz Belzner

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lenz Belzner

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

All Works

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20 of 20 papers shown

1.

Belzner, Lenz, et al.. (2025). The Evolution of Criticality in Deep Reinforcement Learning. 217–224.

2.

Phan, Thomy, et al.. (2024). Emergent cooperation from mutual acknowledgment exchange in multi-agent reinforcement learning. Autonomous Agents and Multi-Agent Systems. 38(2). 2 indexed citations

3.

Gonçalves, José, Lenz Belzner, Łukasz Grewling, et al.. (2022). Alternaria spore exposure in Bavaria, Germany, measured using artificial intelligence algorithms in a network of BAA500 automatic pollen monitors. The Science of The Total Environment. 861. 160180–160180. 10 indexed citations

4.

Phan, Thomy, et al.. (2021). VAST: Value Function Factorization with Variable Agent Sub-Teams. Neural Information Processing Systems. 34. 5 indexed citations

5.

Phan, Thomy, et al.. (2021). Resilient Multi-Agent Reinforcement Learning with Adversarial Value Decomposition. Proceedings of the AAAI Conference on Artificial Intelligence. 35(13). 11308–11316. 12 indexed citations

6.

Phan, Thomy, et al.. (2021). A Sustainable Ecosystem through Emergent Cooperation in Multi-Agent Reinforcement Learning. 2 indexed citations

7.

Müller, Robert, et al.. (2021). Distributed Emergent Agreements with Deep Reinforcement Learning. 1–8. 2 indexed citations

8.

Belzner, Lenz, et al.. (2020). Multi-agent Reinforcement Learning for Bargaining under Risk and Asymmetric Information. 144–151. 1 indexed citations

9.

Gabor, Thomas, et al.. (2020). The Holy Grail of Quantum Artificial Intelligence. 456–461. 12 indexed citations

10.

Phan, Thomy, et al.. (2019). Distributed Policy Iteration for Scalable Approximation of Cooperative Multi-Agent Policies. arXiv (Cornell University). 2162–2164. 1 indexed citations

11.

Gabor, Thomas, et al.. (2019). Self-Replication in Neural Networks. 424–431. 1 indexed citations

12.

Gabor, Thomas, et al.. (2019). Self-Replication in Neural Networks. 424–431. 1 indexed citations

13.

Phan, Thomy, et al.. (2019). Memory Bounded Open-Loop Planning in Large POMDPs Using Thompson Sampling. Proceedings of the AAAI Conference on Artificial Intelligence. 33(1). 7941–7948. 4 indexed citations

14.

Phan, Thomy, et al.. (2018). Leveraging Statistical Multi-Agent Online Planning with Emergent Value Function Approximation. Adaptive Agents and Multi-Agents Systems. 730–738. 3 indexed citations

15.

Waschneck, Bernd, André Reichstaller, Lenz Belzner, et al.. (2018). Deep reinforcement learning for semiconductor production scheduling. Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft). 301–306. 84 indexed citations

16.

Waschneck, Bernd, André Reichstaller, Lenz Belzner, et al.. (2018). Optimization of global production scheduling with deep reinforcement learning. Procedia CIRP. 72. 1264–1269. 264 indexed citations breakdown →

17.

Belzner, Lenz & Thomas Gabor. (2017). Bayesian verification under model uncertainty. 10–13. 2 indexed citations

18.

Gabor, Thomas, et al.. (2016). A Simulation-Based Architecture for Smart Cyber-Physical Systems. 374–379. 186 indexed citations

19.

Belzner, Lenz, et al.. (2016). Software engineering for distributed autonomous real-time systems. 54–57. 3 indexed citations

20.

Belzner, Lenz. (2013). Action Programming In Rewriting Logic.. Theory and Practice of Logic Programming. 13. 1 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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