Computing with chemlambda, the first year

Approximately a year ago I wrote the post A chemical concrete machine for lambda calculus. Quote:

How can this be done? Here is sketch, mind you that I propose things which I believe are possible from a chemical perspective, but I don’t have any chemistry knowledge.  If you do, and if you are interested to make a chemical concrete machine for graphic lambda calculus, then please contact me.

(1) What has been achieved in one year?    (2) What will happen next?

(1) More than 100 posts in the chorasimilarity open notebook  cover, with lots of details, everything which will be mentioned further.

I am most grateful for the collaboration with Louis Kauffman. This was a dream for me since I wrote Computing with space: a tangle formalism for chora and difference. Via the continuous enthusiastic social web connector Stephen P. King, we started to work together and we are now in position, after a year, to take a big leap. We wrote two articles GLC actors, artificial chemical connectomes, topological issues and knots , which is for the moment a not very well understood hidden treasure of a distributed computing model, and Chemlambda, universality and self-multiplication, which will be presented at ALIFE 14, concentrating on the self-multiplication phenomenon (see the last post of the thread of expository posts on this here). These works are embedded into hundreds of hours of discussions with many people. These discussions helped at least as motivations for well explaining things.

In parallel the chemlambda paper was published on figshare: Chemical concrete machine. Follwed by Zipper logic, another piece of the puzzle.

We had a NSF proposal which was centered around cybersecurity, perhaps too early in the stage of development of the project. However, the theoretical part of the project has been appreciated beyond my expectations, what is needed is the practical implementation.


(2) More and more I become convinced that the distributed, decentralized computing project based on chemlambda would be possible today, provided is done in the right place and frame. The most recent thoughts are about the use of the semantic web tools like RDF and N3logic for this (although I strongly believe in the no semantics slogan).

I shall write much more in a part II post, right now I have a very bad connection…

UPDATE: … so, imagine that chemlambda molecules are RDF datasets, accesible via the respective URI. If you want to run a computation then you need to impersonate the actors (because the initial actor diagram is already in the structure of the RDF dataset) and to specify a model of computation (i.e. to specify the reduction rules decorated with actors, along with the actors behaviours, all in N3).

Well designed computations could then have their URIs.

Then, imagine that you want to endow your computer with a microbiome OS, just follow the links.

Another, related direction of future research concerns the IoT, things and space ….



2 thoughts on “Computing with chemlambda, the first year”

    1. Hi Stephen, I am in favor of using a standard RDF format for molecules and their initial actor diagram (i.e. a RDF dataset). Then, regarding names, the actors are programs like those which implement the TCP (and UDP) protocol, which are available at an web address, the gui is the equivalent of a browser program, also available at an web address and the RDF datasets have also their URIs. If you want to deploy a computation over the web then you have to get a representation of the graphs and actors diagrams and run them with a dedicated program. This is a whole ecosystem, scalable in this way.

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