AFA-PredNet: The Action Modulation Within Predictive Coding

Junpei Zhong, Angelo Cangelosi, Xinzheng Zhang, Tetsuya Ogata

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    2 Citations (Scopus)

    Abstract

    The predictive processing (PP) hypothesizes that the predictive inference of our sensorimotor system is encoded implicitly in the regularities between perception and action. We propose a neural architecture in which such regularities of active inference are encoded hierarchically. We further suggest that this encoding emerges during the embodied learning process when the appropriate action is selected to minimize the prediction error in perception. Therefore, this predictive stream in the sensorimotor loop is generated in a top-down manner. Specifically, it is constantly modulated by the motor actions and is updated by the bottom-up prediction error signals. In this way, the top-down prediction originally comes from the prior experience from both perception and action representing the higher levels of this hierarchical cognition. In our proposed embodied model, we extend the PredNet Network, a hierarchical predictive coding network, with the motor action units implemented by a multi-layer perceptron network (MLP) to modulate the network top-down prediction. Two experiments, a minimalistic world experiment, and a mobile robot experiment are conducted to evaluate the proposed model in a qualitative way. In the neural representation, it can be observed that the causal inference of predictive percept from motor actions can be also observed while the agent is interacting with the environment.

    Original languageEnglish
    Title of host publication2018 International Joint Conference on Neural Networks, IJCNN 2018 - Proceedings
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Volume2018-July
    ISBN (Electronic)9781509060146
    DOIs
    Publication statusPublished - 2018 Oct 10
    Event2018 International Joint Conference on Neural Networks, IJCNN 2018 - Rio de Janeiro, Brazil
    Duration: 2018 Jul 82018 Jul 13

    Other

    Other2018 International Joint Conference on Neural Networks, IJCNN 2018
    CountryBrazil
    CityRio de Janeiro
    Period18/7/818/7/13

    ASJC Scopus subject areas

    • Software
    • Artificial Intelligence

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  • Cite this

    Zhong, J., Cangelosi, A., Zhang, X., & Ogata, T. (2018). AFA-PredNet: The Action Modulation Within Predictive Coding. In 2018 International Joint Conference on Neural Networks, IJCNN 2018 - Proceedings (Vol. 2018-July). [8489751] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IJCNN.2018.8489751