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Revisiting the XOR problem: a neurorobotic implementation

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Abstract

The exclusive-or (XOR) classification task still represents a challenge in the study of cognition since the precise neural circuit sustaining the general ability to learn nonlinear problems remains to be discovered in natural organisms. As such, this paper focuses on a neurorobotic application embedding a specific spiking neural network built to solve these types of tasks. This experiment proposes a 2-bit task (XOR) with visual compound binary images acting as inputs and a left/right action for the output. The robot learns to solve it in both virtual and real environments from an operant conditioning procedure. Furthermore, the robot also adapts its behavior from learning all other simpler associative rules, even when switching them at runtime. Finally, this study explores the impact on the neural architecture, when passing from a 2-bit to a 3-bit task.

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Authors and Affiliations

  1. Ottawa University, 75 Laurier Avenue East, Ottawa, ON, K1N 6N5, Canada

    André Cyr & Sylvain Chartier

  2. Cégep du Vieux Montréal, 255 Ontario Est, Montréal, QC, H2X 1X6, Canada

    Frédéric Thériault

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  1. André Cyr
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  2. Frédéric Thériault
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  3. Sylvain Chartier
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Correspondence to André Cyr.

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Cyr, A., Thériault, F. & Chartier, S. Revisiting the XOR problem: a neurorobotic implementation. Neural Comput & Applic 32, 9965–9973 (2020). https://doi.org/10.1007/s00521-019-04522-0

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  • DOI: https://doi.org/10.1007/s00521-019-04522-0

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