Noa Agmon

2.0k total citations
73 papers, 1.2k citations indexed

About

Noa Agmon is a scholar working on Computer Networks and Communications, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Noa Agmon has authored 73 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Computer Networks and Communications, 31 papers in Artificial Intelligence and 28 papers in Computer Vision and Pattern Recognition. Recurrent topics in Noa Agmon's work include Optimization and Search Problems (32 papers), Robotic Path Planning Algorithms (27 papers) and Distributed Control Multi-Agent Systems (17 papers). Noa Agmon is often cited by papers focused on Optimization and Search Problems (32 papers), Robotic Path Planning Algorithms (27 papers) and Distributed Control Multi-Agent Systems (17 papers). Noa Agmon collaborates with scholars based in Israel, United States and Italy. Noa Agmon's co-authors include Gal A. Kaminka, Sarit Kraus, David Peleg, Yehuda Elmaliach, Peter Stone, Noam Hazon, Samuel Barrett, Daniel Urieli, Mor Vered and O. Maksimov and has published in prestigious journals such as Artificial Intelligence, The International Journal of Robotics Research and SIAM Journal on Computing.

In The Last Decade

Noa Agmon

67 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Noa Agmon Israel	17	746	497	296	277	239	73	1.2k
Nilanjan Chakraborty United States	19	528 0.7×	363 0.7×	240 0.8×	180 0.6×	270 1.1×	82	1.4k
Amanda Prorok United Kingdom	21	669 0.9×	540 1.1×	433 1.5×	328 1.2×	169 0.7×	59	1.5k
Adrian Agogino United States	26	215 0.3×	120 0.2×	481 1.6×	299 1.1×	489 2.0×	81	1.5k
Asif Khan India	13	358 0.5×	397 0.8×	147 0.5×	354 1.3×	35 0.1×	49	850
Chenglie Du China	16	354 0.5×	259 0.5×	175 0.6×	216 0.8×	39 0.2×	98	1.0k
Stephen Balakirsky United States	18	148 0.2×	408 0.8×	386 1.3×	257 0.9×	249 1.0×	97	1.2k
TaeChoong Chung South Korea	14	177 0.2×	234 0.5×	216 0.7×	103 0.4×	31 0.1×	61	727
Takeshi Hatanaka Japan	16	758 1.0×	221 0.4×	76 0.3×	213 0.8×	205 0.9×	149	1.2k
Félix Ingrand France	17	259 0.3×	445 0.9×	761 2.6×	145 0.5×	291 1.2×	45	1.6k
Bing-Hong Liu Taiwan	22	755 1.0×	95 0.2×	151 0.5×	74 0.3×	36 0.2×	71	1.5k

Countries citing papers authored by Noa Agmon

Since Specialization

Citations

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

Fields of papers citing papers by Noa Agmon

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Noa Agmon

This figure shows the co-authorship network connecting the top 25 collaborators of Noa Agmon. A scholar is included among the top collaborators of Noa Agmon 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 Noa Agmon. Noa Agmon 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

Zivan, Roie, et al.. (2024). Collision Avoiding Max-Sum for Mobile Sensor Teams. Journal of Artificial Intelligence Research. 79. 1281–1311. 1 indexed citations

Agmon, Noa, et al.. (2020). Non-Uniform Policies for Multi-Robot Asymmetric Perimeter Patrol in Adversarial Domains. Adaptive Agents and Multi-Agents Systems. 983–991.

Louzoun, Yoram, et al.. (2020). Explicit Gradient Learning for Black-Box Optimization. International Conference on Machine Learning. 1. 8480–8490. 2 indexed citations

Agmon, Noa, et al.. (2018). Scheduling Spare Drones for Persistent Task Performance under Energy Constraints. Adaptive Agents and Multi-Agents Systems. 532–540. 13 indexed citations

Agmon, Noa, et al.. (2017). Safety First: Strategic Navigation in Adversarial Environments. Adaptive Agents and Multi-Agents Systems. 1581–1583. 1 indexed citations

Agmon, Noa, et al.. (2015). Adversarial Modeling in the Robotic Coverage Problem. Adaptive Agents and Multi-Agents Systems. 891–899. 3 indexed citations

Agmon, Noa, et al.. (2015). Frontier-Based RTDP: A New Approach to Solving the Robotic Adversarial Coverage Problem. Adaptive Agents and Multi-Agents Systems. 861–869. 4 indexed citations

Agmon, Noa, Samuel Barrett, & Peter Stone. (2014). Modeling uncertainty in leading ad hoc teams. Adaptive Agents and Multi-Agents Systems. 397–404. 10 indexed citations

Agmon, Noa, et al.. (2014). Effective, quantitative, obscured observation-based faultdetection in multi-agent systems. Adaptive Agents and Multi-Agents Systems. 1449–1450. 1 indexed citations

10.

Barrett, Samuel, Noa Agmon, Noam Hazon, Sarit Kraus, & Peter Stone. (2014). Communicating with unknown teammates. Adaptive Agents and Multi-Agents Systems. 1433–1434. 12 indexed citations

11.

Agmon, Noa & Peter Stone. (2012). Leading ad hoc agents in joint action settings with multiple teammates. Adaptive Agents and Multi-Agents Systems. 341–348. 28 indexed citations

12.

Agmon, Noa & Peter Stone. (2011). Leading multiple ad hoc teammates in joint action settings. National Conference on Artificial Intelligence. 2–8. 3 indexed citations

13.

Agmon, Noa, Daniel Urieli, & Peter Stone. (2011). Ship patrol: multiagent patrol under complex environmental conditions. Adaptive Agents and Multi-Agents Systems. 1103–1104. 1 indexed citations

14.

Kaminka, Gal A., et al.. (2011). Who goes there?: selecting a robot to reach a goal using social regret. Adaptive Agents and Multi-Agents Systems. 91–98. 2 indexed citations

15.

Agmon, Noa. (2010). On events in multi-robot patrol in adversarial environments. Adaptive Agents and Multi-Agents Systems. 591–598. 13 indexed citations

16.

Agmon, Noa, et al.. (2009). Of robot ants and elephants. Adaptive Agents and Multi-Agents Systems. 81–88. 7 indexed citations

17.

Agmon, Noa, et al.. (2009). Adversarial uncertainty in multi-robot patrol. International Joint Conference on Artificial Intelligence. 1811–1817. 33 indexed citations

18.

Agmon, Noa, et al.. (2008). The impact of adversarial knowledge on adversarial planning in perimeter patrol. Adaptive Agents and Multi-Agents Systems. 55–62. 58 indexed citations

19.

Agmon, Noa, Gal A. Kaminka, & Sarit Kraus. (2005). Team member reallocation via tree pruning. National Conference on Artificial Intelligence. 35–40. 1 indexed citations

20.

Agmon, Noa & David Peleg. (2004). Fault-tolerant gathering algorithms for autonomous mobile robots. Symposium on Discrete Algorithms. 1070–1078. 17 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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