Priya S. & Nehaniv C. L. (2020) Life-span expectancy and cycle size in the original autopoiesis algorithm. In: Bongard J., Lovato J., Soros L. & Hebert-Dufrésne L. (eds.) Proceedings of the 2020 Conference on Artificial Life (ALIFE 2020). MIT Press, Cambridge MA: 69–77. https://cepa.info/7616
Priya S. & Nehaniv C. L.
(
2020)
Life-span expectancy and cycle size in the original autopoiesis algorithm.
In: Bongard J., Lovato J., Soros L. & Hebert-Dufrésne L. (eds.) Proceedings of the 2020 Conference on Artificial Life (ALIFE 2020). MIT Press, Cambridge MA: 69–77.
Fulltext at https://cepa.info/7616
We implement Varela, Maturana and Uribe’s original autopoiesis algorithm with suitable modifications as proposed by McMullin. We further investigate how environmental factors affect formation of autopoietic entities – namely how long an entity remains a whole after formation and to what size does it grow in its life span i.e. Life span and Cycle size respectively. We find that ratios of different basic elements like Holes, Substrates and Catalysts do not affect Life span and Cycle size meaningfully but both properties are affected negatively if disintegration probability – the probability of a Link element to transform into a Substrate element – is increased.
Quick T., Dautenhahn K., Nehaniv C. & Roberts G. (1999) On bots and bacteria: Ontology independent embodiment [Construction of one’s own reality]. In: Floreano D., Nicoud J.-D. & Mondada F. (eds.) Advances in artificial life: Proceedings of the Fifth European Conference on Artificial Life. Springer, Heidelberg: 339–343. https://cepa.info/7277
Quick T., Dautenhahn K., Nehaniv C. & Roberts G.
(
1999)
On bots and bacteria: Ontology independent embodiment [Construction of one’s own reality].
In: Floreano D., Nicoud J.-D. & Mondada F. (eds.) Advances in artificial life: Proceedings of the Fifth European Conference on Artificial Life. Springer, Heidelberg: 339–343.
Fulltext at https://cepa.info/7277
A framework for understanding and exploiting embodiment is presented which is not dependent on any specific ontological context. This framework is founded on a new definition of embodiment, based on the relational dynamics that exist between biological organisms and their environments, and inspired by the structural dynamics of the bacterium Escherichia coli. Full recognition is given to the role played by physically instantiated bodies, but in such a way that this can be meaningfully abstracted within the constraints implied by the term ‘embodiment’, and applied in a variety of operational contexts. This is illustrated by ongoing experimental work in which the relational dynamics that exist between E. coli and its environment are applied in a variety of software environments, using Cellular Automata (CA) with artificial’ sensory’ and’ effector’ surfaces, producing qualitatively similar’ chemotactic’ behaviours in a variety of operational domains.