SYMBIOSIS & BIOCOMPUTING SYSTEMS / video

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The authors have continued developing Symbiotic Architecture Project. In June 2015, they have participated at the STRAND conference “Going Digital: Innovations in the Contemporary Life” where they discussed biocomputing systems within the Symbiosis.

Antonio Gaudi once said: “Nothing is art if it does not come from nature.” Following this and the idea that “the nature is our book of references” as Frank Lloyd Wright wrote, we are looking into nature’s processes and learning from them. Analyzing cells – their essence, behaviour, movement and form transformation according to their own needs – we notice that the substance is not the only factor. It is induced by the impulses which define its elasticity, form transformability and self-sustainability. Those impulses could be understood as indicators of hypothetical biocomputing systems.

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Biocomputing, biomolecular computing or computations performed by biomolecules are becoming our reality. The idea of storing data on a molecular level is not new. Back in the late 1940s, mathematician John von Neumann discussed the theory of self-reproducing automata, the idea of a machine creating a more complex machine. For us, biocomputing is a wider theoretical term. We consider all nature processes – from the behaviour of simple one-cell organism to the impulses of human brain – a specific kinds of biological computers.

Stanisław Lem, a Polish writer, argues the idea of intelligence in nature. “Non-intelligent” beings use inherited regulation mechanisms to adapt themselves to the environmental phenomena. When it comes to the scope of possible responses to the changes, they are “programmed in advance” to obtain their continuity. Yet, those mechanisms can respond only to the genetically predefined conditions. When faced with the new problem solving or changed conditions instinctive behaviour looses its preciseness. Advantage is then given to the “intelligent” beings that have the ability to change their acting programs according to their own needs. Lem defines this as “self-programming by learning”. They no longer have predefined knowledge. Instead, they need to learn the best way of acting. Even though is has its own risks, this kind of behaviour is more adaptable to the modulating surroundings. We consider both categories, programmed in advance and self-programmed by learning, types of biocomputing possibilities.

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Walls of symbiotic architecture represent the unity of biochemical substances and biocomputing mechanisms and produce a self sustained energy source as a result of the initial interaction. When talking about biocomputing mechanisms, we relate to Lem’s discussions about intelligence in nature. Symbiotic architecture biocomputational elements have both the “genetically” pre-programmed intuition and the ability to learn and self-programme in cases of unexpected changes.

Symbiotic architecture is a symbiosis between “programmed in advance” systems and “self-programmed by learning” systems. First level systems represent symbiotic membrane – a body, a house – and function upon previously genetically defined intuitional impulses. The membrane reacts to the elementary needs and responds to the basic changes. Second level systems represent other symbiote – a spirit, an initiator, a man. This symbiote, along with the third symbiote nature, gives a house a possibility of learning and by that, possibilities for responding to more demanding needs and unpredictable changes.

Authors: Ksenija Bulatovic, Ksenija Bunjak, Sasa Naumovic

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