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Choice modeling using dot-product attention mechanism

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Abstract

Modelling the cognitive process is a challenging task. Contextual conditions and the scope of the options are critical factors that influence human decisions. We propose and formulate an attention-based network to model the various choices made by humans based on the various factors that predict the possible option in each scope. To evaluate our proposed method, we conducted a user choice experiment in which a user chose an option from among limited choices. Our results showed that our model successfully extracted the hidden context on the attention layer and even outperformed the chance level in terms of prediction accuracy.

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Acknowledgements

This work was supported by Grant-in-Aid for Scientific Research on Innovative Areas, Grant numbers 19H05693

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Authors and Affiliations

  1. Osaka University, 1-3, Machikaneyama, Toyonaka, Osaka, 560-8531, Japan

    Mofei Li, Yutaka Nakamura & Hiroshi Ishiguro

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  1. Mofei Li
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  2. Yutaka Nakamura
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  3. Hiroshi Ishiguro
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Correspondence to Yutaka Nakamura.

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This work was presented in part at the 25th International Symposium on Artificial Life and Robotics (Beppu, Oita, January 22–24, 2020).

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Li, M., Nakamura, Y. & Ishiguro, H. Choice modeling using dot-product attention mechanism. Artif Life Robotics 26, 116–121 (2021). https://doi.org/10.1007/s10015-020-00638-y

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