Abstract
We wish to use Artificial Chemistries to build and investigate open-ended systems. As such, we wish to minimise the number of explicit rules and properties needed. We describe here the concept of sub-symbolic Artificial Chemistries (ssAChems), where reaction properties are emergent properties of the internal structure and dynamics of the component particles. We define the components of a ssAChem, and illustrate it with two examples: RBN-world, where the particles are Random Boolean Networks, the emergent properties come from the dynamics on an attractor cycle, and composition is through rewiring the components to form a larger RBN; and SMAC, where the particles are Hermitian matrices, the emergent properties are eigenvalues and eigenvectors, and composition is through the non-associative Jordan product. We conclude with some ssAChem design guidelines.
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Notes
- 1.
To follow our design criteria, we should choose a non-arbitrary element. Future work includes developing a choice criterion for this.
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Acknowledgements
Faulkner is funded by an York Chemistry Department Teaching PhD studentship. Krastev is funded by a York Computer Science Department EPSRC DTA PhD studentship. We thank Leo Caves for some insightful comments on this work. We thank Michael Krotosky, Andrew Balin, and Rudi Mears for their work in exploring some earlier versions of ideas presented here.
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Faulkner, P., Krastev, M., Sebald, A., Stepney, S. (2018). Sub-Symbolic Artificial Chemistries. 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_14
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