Measuring Spatial Behaviour and Cognition: A Method Based on Trajectories Analysis and Supported by Technology and Artificial Intelligence | SpringerLink
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Measuring Spatial Behaviour and Cognition: A Method Based on Trajectories Analysis and Supported by Technology and Artificial Intelligence

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Bioinspired Systems for Translational Applications: From Robotics to Social Engineering (IWINAC 2024)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14675))

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Abstract

Spatial cognition is a fundamental cognitive process for adapting to the environment, and it has been extensively researched in humans, animals, and artificial agents using various methods, such as clinical and comparative studies. Spatial cognition and related skills can be deduced from behaviours, such as reaching for an object, returning to a familiar area after an extended run, or identifying the corner in an enclosure where food is hidden.

In this paper, we will propose a method based on trajectory analysis with index calculation and we will illustrate two examples of applying this method 1) to a neuro-psychological test and 2) analyzing the performance of agents in a behavioural task. The results suggest that this method can complement traditional measures of spatial cognition.

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Authors and Affiliations

  1. NAC Lab Orazio Miglino, Department of Humanistic Studies, University of Naples “Federico II”, Naples, Italy

    Michela Ponticorvo, Maria Luongo, Antonietta Argiuolo & Onofrio Gigliotta

Authors
  1. Michela Ponticorvo
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  2. Maria Luongo
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  3. Antonietta Argiuolo
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  4. Onofrio Gigliotta
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Corresponding author

Correspondence to Michela Ponticorvo .

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Editors and Affiliations

  1. Universidad Politécnica de Cartagena, Cartagena, Spain

    José Manuel Ferrández Vicente

  2. Polytechnic University of Valencia, Valencia, Spain

    Mikel Val Calvo

  3. Ohio State University, Columbus, OH, USA

    Hojjat Adeli

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Ponticorvo, M., Luongo, M., Argiuolo, A., Gigliotta, O. (2024). Measuring Spatial Behaviour and Cognition: A Method Based on Trajectories Analysis and Supported by Technology and Artificial Intelligence. In: Ferrández Vicente, J.M., Val Calvo, M., Adeli, H. (eds) Bioinspired Systems for Translational Applications: From Robotics to Social Engineering. IWINAC 2024. Lecture Notes in Computer Science, vol 14675. Springer, Cham. https://doi.org/10.1007/978-3-031-61137-7_37

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  • DOI: https://doi.org/10.1007/978-3-031-61137-7_37

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