Abstract
Slime mould of Physarum polycephalum is a large cell exhibiting rich spatial non-linear electrical characteristics. We exploit the electrical properties of the slime mould to implement logic gates using a flexible hardware platform designed for investigating the electrical properties of a substrate (Mecobo). We apply arbitrary electrical signals to ‘configure’ the slime mould, i.e. change shape of its body and, measure the slime mould’s electrical response. We show that it is possible to find configurations that allow the Physarum to act as any 2-input Boolean gate. The occurrence frequency of the gates discovered in the slime was analysed and compared to complexity hierarchies of logical gates obtained in other unconventional materials. The search for gates was performed by both sweeping across configurations in the real material as well as training a neural network-based model and searching the gates therein using gradient descent.
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Notes
- 1.
ReLU: Rectified Linear Unit.
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Acknowledgements
The research leading to these results has received funding from the EC FP7 under grant agreements 317662 (NASCENCE project) and 316366 (PHYCHIP project).
The authors would like to acknowledge the assistance of Odd Rune Lykkebø for his technical assistance with Mecobo. Simon and Andy prepared the mould and performed the exhaustive search experiments on the hardware platform, Jan, Klaus and Jürgen contributed with the mould neural network modelling.
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Harding, S., Koutník, J., Schmidhuber, J., Adamatzky, A. (2018). Discovering Boolean Gates in Slime Mould. In: Stepney, S., Adamatzky, A. (eds) Inspired by Nature. Emergence, Complexity and Computation, vol 28. Springer, Cham. https://doi.org/10.1007/978-3-319-67997-6_15
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