Countries citing papers authored by Matthias Scheutz
Since
Specialization
Citations
This map shows the geographic impact of Matthias Scheutz'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 Matthias Scheutz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthias Scheutz more than expected).
Fields of papers citing papers by Matthias Scheutz
This network shows the impact of papers produced by Matthias Scheutz. 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 Matthias Scheutz. The network helps show where Matthias Scheutz may publish in the future.
Co-authorship network of co-authors of Matthias Scheutz
This figure shows the co-authorship network connecting the top 25 collaborators of Matthias Scheutz.
A scholar is included among the top collaborators of Matthias Scheutz 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 Matthias Scheutz. Matthias Scheutz is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Briggs, Gordon & Matthias Scheutz. (2016). The Pragmatic Social Robot: Toward Socially-Sensitive Utterance Generation in Human-Robot Interactions.. National Conference on Artificial Intelligence.9 indexed citations
11.
Williams, Tom & Matthias Scheutz. (2015). A Domain-Independent Model of Open-World Reference Resolution.. Cognitive Science.4 indexed citations
12.
Núñez, Rafael C., Matthias Scheutz, Gordon Briggs, et al.. (2013). DS-based uncertain implication rules for inference and fusion applications. International Conference on Information Fusion. 1934–1941.9 indexed citations
13.
Scheutz, Matthias, et al.. (2012). Neural Circuits for Any-Time Phrase Recognition with Applications in Cognitive Models and Human-Robot Interaction. Cognitive Science. 34(34).2 indexed citations
14.
Boyer, Ty W., Matthias Scheutz, & Bennett I. Bertenthal. (2009). Dissociating Ideomotor and Spatial Compatibility: Empirical Evidence and Connectionist Models. Proceedings of the Annual Meeting of the Cognitive Science Society. 31(31).5 indexed citations
15.
Schermerhorn, Paul, et al.. (2006). DIARC: a testbed for natural human-robot interaction. National Conference on Artificial Intelligence. 1972–1973.31 indexed citations
16.
Scheutz, Matthias & Paul Schermerhorn. (2005). Many is more: The utility of simple reactive agents with predictive mechanisms in multiagent object collection tasks. Web Intelligence and Agent Systems An International Journal. 3(2). 97–116.5 indexed citations
17.
Scheutz, Matthias. (2004). The Role of Signaling Action Tendencies in Conflict Resolution. Journal of Artificial Societies and Social Simulation. 7(1). 1–4.4 indexed citations
18.
Kramer, James & Matthias Scheutz. (2003). GLUE - A Component Connecting Schema-based Reactive to Higher-level Deliberative Layers for Autonomous Agents.. The Florida AI Research Society. 49(2). 22–26.2 indexed citations
19.
Scheutz, Matthias. (2002). Agents with or without Emotions. The Florida AI Research Society. 89–93.13 indexed citations
20.
Scheutz, Matthias. (2002). Affective Action Selection and Behavior Arbitration for autonomous Robots.. International Conference on Artificial Intelligence. 334–340.9 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.