Biologically Inspired Cognitive Architectures

290 papers and 2.1k indexed citations i.

About

The 290 papers published in Biologically Inspired Cognitive Architectures in the last decades have received a total of 2.1k indexed citations. Papers published in Biologically Inspired Cognitive Architectures usually cover Artificial Intelligence (163 papers), Cognitive Neuroscience (119 papers) and Social Psychology (40 papers) specifically the topics of Neural dynamics and brain function (47 papers), Cognitive Science and Mapping (46 papers) and AI-based Problem Solving and Planning (39 papers). The most active scholars publishing in Biologically Inspired Cognitive Architectures are Alexei V. Samsonovich, Jan Treur, Paul F. M. J. Verschure, Debashis Das Chakladar, Edmund T. Rolls, Sanjay Chakraborty, Stan Franklin, Ignazio Infantino, Filippo Vella and Jeffrey L. Krichmar.

In The Last Decade

Fields of papers published in Biologically Inspired Cognitive Architectures

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Biologically Inspired Cognitive Architectures. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Biologically Inspired Cognitive Architectures.

Countries where authors publish in Biologically Inspired Cognitive Architectures

Since Specialization
Citations

This map shows the geographic impact of research published in Biologically Inspired Cognitive Architectures. 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 papers published in Biologically Inspired Cognitive Architectures with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Biologically Inspired Cognitive Architectures more than expected).

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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2025