Cognitive Systems Research

Papers
(The H4-Index of Cognitive Systems Research is 21. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2022-06-01 to 2026-06-01.)
ArticleCitations
Editorial Board157
The mode of computing81
Creating AI-generated role-playing videos from causal network model simulations of social anxiety disorder for virtual therapeutic contexts59
Long horizon episodic decision making for cognitively inspired robots54
Conceptual development from the perspective of a brain-inspired robotic architecture51
DDG: Dependency-difference gait based on emotional information attention for perceiving emotions from gait50
Deconstructing emotions in self-control through computational modeling47
Computational modeling of organisational learning by self-modeling networks43
Adaptive timing in a dynamic field architecture for natural human–robot interactions40
Adaptive network modeling of the influence of leadership and communication on learning within an organization39
A study of conceptual primitive elimination: Embedding INGEST into PTRANS37
The Chinese character illusion36
Analogical mappings of facts and counterfactuals in the human mind and Peirce’s abduction: limitations in LLMs33
Retraction notice to “Fuzzy cluster correlation mapping for online evaluation of teaching efficacy towards IoT study” [Cogn. Syst. Res. 52 (2018) 365–370]32
Quantum projections on conceptual subspaces24
Towards generalization in subitizing with neuro-symbolic loss using holographic reduced representations23
An adaptive network model of the role of the microbiome-gut-brain axis in insomnia23
Retraction notice to “An optimized reconfigurable algorithm for FPGA architecture oriented IoT applications” [Cogn. Syst. Res. 52 (2018) 335–341]23
Computational modeling of bloodstream biomarker kinetics as a basis for motivated behavior in the regulation of hunger and thirst22
Characterising cognitively useful blends: Formalising governing principles of conceptual blending21
Eliciting metaknowledge in Large Language Models21
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