Countries citing papers authored by Adrian Agogino
Since
Specialization
Citations
This map shows the geographic impact of Adrian Agogino'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 Adrian Agogino with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Adrian Agogino more than expected).
This network shows the impact of papers produced by Adrian Agogino. 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 Adrian Agogino. The network helps show where Adrian Agogino may publish in the future.
Co-authorship network of co-authors of Adrian Agogino
This figure shows the co-authorship network connecting the top 25 collaborators of Adrian Agogino.
A scholar is included among the top collaborators of Adrian Agogino 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 Adrian Agogino. Adrian Agogino is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Sabelhaus, Andrew P. & Adrian Agogino. (2018). Inverse Kinematics for Control of Tensegrity Soft Robots: Existence and Optimality of Solutions.. arXiv (Cornell University).2 indexed citations
3.
Sabelhaus, Andrew P., et al.. (2018). Model-Predictive Control with Reference Input Tracking for Tensegrity Spine Robots.. arXiv (Cornell University).1 indexed citations
Sabelhaus, Andrew P., Jonathan Bruce, Ken Caluwaerts, et al.. (2014). Hardware Design and Testing of SUPERball, A Modular Tensegrity Robot. 81(3). 352–5.12 indexed citations
Tumer, Kagan & Adrian Agogino. (2008). Adaptive management of air traffic flow: a multiagent coordination approach. National Conference on Artificial Intelligence. 1581–1584.5 indexed citations
Agogino, Adrian & Kagan Tumer. (2006). QUICR-learning for multi-agent coordination. National Conference on Artificial Intelligence. 1438–1443.11 indexed citations
17.
Tumer, Kagan & Adrian Agogino. (2006). Agent Reward Shaping for Alleviating Traffic Congestion. Autonomous Agents and Multi-Agent Systems.5 indexed citations
Agogino, Adrian & Kagan Tumer. (2005). Quicker Q-Learning in Multi-Agent Systems. International Joint Conference on Artificial Intelligence.4 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.