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An introduction to brain emotional learning inspired models (BELiMs) with an example of BELiMs’ applications

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Abstract

Brain emotional learning-inspired models (BELiMs) is a new category of computational intelligence (CI) paradigms. The general structure of BELiMs is based on the neural structure of the emotion system which processes and evaluates fear-induced stimuli, to produce emotional responses. The function of a BELiM is implemented by assigning adaptive networks to different parts of its structure. The primary motivation for developing BELiMs is to address model and time complexity issues associated with supervised machine learning artificial neural networks and neuro-fuzzy methods. One of the applications of BELiMs is chaotic time series prediction problems. A BEliM can be used as a time series prediction model. This paper introduces BELiMs as a new CI paradigm and explains historical, theoretical, structural and functional aspects of BELiMs. I also validate and evaluate the performance of BELiMs as a time series prediction model by examining different variations of BELiMs on benchmark time series data sets and comparing obtained results with different CI models.

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Notes

  1. Which means that they need a large number of computational resources for solving problems.

  2. It is responsible for generating fear reactions and is an essential component of a mammal’s survival circuit.

  3. It can be considered as one function of the emotional system of fear, is a kind of behaviour that an organism presents to predict aversive events by learning a connection between an aversive stimulus and a neutral stimulus (Maren 2001).

  4. Walter Bradford Cannon was a physiologist at Harvard University, and Philip Bard was a doctoral student of Cannon.

  5. James Wenceslas Papez was an American neuroanatomist.

  6. Paul D. MacLean was an American physician, and neuroscientist.

  7. It is a behavioural paradigm that is used by mammalians not only to predict the occurrence of fearful stimuli but also to learn to avoid the origins of fearful stimuli.

  8. Computational models of emotions are simulation tools to prove theories of emotions Scherer et al. (2010) (for further reading, please refer to Parsapoor 2015).

  9. The terminology of BELs, first time presented by Parsapoor and Bilstrup (2013c).

  10. An extended abstract submitted in FORGES-2008 (http://crd.yerphi.am/FORGES2008).

  11. The paper completely explained BELRFS and presented its results as a time series prediction model and compared its obtained results with powerful MLs such as ANFIS.

  12. Where (x(t), y(t), z(t)) are coordinates in the 3D space. There are three constants as \(\sigma \), \(\rho \) and \(\beta \) and three variables as (x(t), y(t), z(t)).

  13. Sunspots are “cool planet-sized areas on the Sun where intense magnetic loops poke through the star’s visible surface” (The Sunspot Number 2015).

  14. Solar activity forecasting is necessary to predict changes in the space environment between the Earth and Sun and protect damages to space weather and ground-based communication tools.

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Acknowledgements

This paper is a summary version of the author’s licentiate thesis called “Brain emotional Learning-inspired Models” and PhD dissertation entitled “Towards emotion inspired computational intelligence.” Thus, the author would like to express her gratefulness to, Professor Bertil Svensson (my principal supervisor) and Professor Urban Bilstrup (my co-supervisor), who provided her with the precious opportunity to work on and develop BELiMs and complete her PhD thesis. The author would like to offer her sincerest thanks to the late Professor Caro Lucas for his inspiration and kind support in supervising me throughout her research process concerning the development the brain emotional learning- based prediction models. The author is also thankful for the financial support of the Knowledge Foundation and CERES (The Centre for Research on Embedded Systems) Also, the authors are grateful for accessing sunspot number data provided by NOAA and World Data Center for Geomagnetism and Space Magnetism, Kyoto University.

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    Mahboobeh Parsapoor

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Parsapoor, M. An introduction to brain emotional learning inspired models (BELiMs) with an example of BELiMs’ applications. Artif Intell Rev 52, 409–439 (2019). https://doi.org/10.1007/s10462-018-9638-y

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