Tag Archives: information theory

FAQ: chemlambda in real and virtual worlds

Q1. is chemlambda different than previous models, like the algorithmic chemistry of Fontana and Buss, or the CHAM of Berry and Boudol?

A1. Yes. In chemlambda we work with certain graphs made of nodes (atoms) and bond (arrows), call such a graph a  molecule.  Then:

  • (A) We work with individual molecules, not with populations of molecules. The molecules encode information in their shape, not in their number.
  • (B) different from algorithmic chemistry, the application and abstraction are atoms of the molecules.
  • (C) There are no variables in chemlambda and there is no need to introduce one species of molecules per variable, like in the previous models.
  • (D) chemlambda and it’s associated computing model (distributed GLC)  work well in a decentralized world, there is no need for having a global space or a global time for the computation.

There is a number of more technical differences, like (non exhaustively):

  • (E)  molecules  are not identified with their functions. Technically, chemlambda rejects eta reduction, so even for those molecules which represent lambda terms, they are not identified (as happens when we use eta reduction) with their function. This calls for an “extreme” functional programming style.
  • (F) only a small part of the chemlambda molecules correspond to lambda terms (there is a lambda calculus “sector”).
  • (G) there is no  global semantics.

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Q2.  is chemlambda a kind of computing with chemical reaction networks (CRNs)?

A2. No. Superficially, there are resemblances, and really one may imagine CRNs based on chemlambda, but this is not what we are doing.

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Q3. Why do you think chemlambda has something to tell about the real or even about the living world?

A3. Because the real world, in it’s fundamental workings, does not seem to care about 1D language based constructs which we cherish in our explanation. The real and especially the living world seems to be based on local, asynchronous interactions which are much more like signal transductions and much less like information passing. (See How is different signal transduction from information theory? )
Everything happens locally, in nontrivial but physical ways, leading to emergent complex behaviours. Nature does not care about coordinates and names of things or abstractions, unless they are somehow physically embodied. This is the way chemlambda functions.

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Q4. Why do you think chemlambda has something to say about the virtual  world of the Net?

A4. Because it puts the accent on alife instead of AI, on decentralization instead of pyramidal constructs.  A microbial ecology like internet is much more realistic to hope to realize than one based on benevolent pyramidal AI constructs (be them clouds, or other corporations constructs). Because real and virtual worlds are consistent only locally.

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Q5. What about the Internet of Things?

A5. We hope to give to the IoT the role of the bridge which unites two kinds of computations real-virtual, under the same chemistry.

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Q6. What would happen in your dream world?

A6. There are already some (fake) news about it here: what if

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How is different signal transduction from information theory?

They look different.

“Signal transduction occurs when an extracellular signaling[1] molecule activates a specific receptor located on the cell surface or inside the cell. In turn, this receptor triggers a biochemical chain of events inside the cell, creating a response.[2] Depending on the cell, the response alters the cell’s metabolism, shape, gene expression, or ability to divide.[3] The signal can be amplified at any step. Thus, one signaling molecule can cause many responses.[4]

Signal transduction involves the binding of extracellular signalling molecules and ligands to cell-surface receptors that trigger events inside the cell. The combination of messenger with receptor causes a change in the conformation of the receptor, known as receptor activation. This activation is always the initial step (the cause) leading to the cell’s ultimate responses (effect) to the messenger. Despite the myriad of these ultimate responses, they are all directly due to changes in particular cell proteins. Intracellular signaling cascades can be started through cell-substratum interactions; examples are the integrin that binds ligands in the extracellular matrix and steroids.[13]

[wiki source]

 

It seems that signal transduction involves:

  • messenger molecule
  • receptor molecule
  • the messenger reacts with the receptor, which changes conformation (receptor activation)
  • receptor activation triggers other chemical reactions

Let’s condense further:

  • molecule M (messenger) binds to molecule R (receptor)
  • the complex MR changes shape (a spatial notion, in a generalized sense)
  • which triggers other reactions between (the new) R with other neighboring molecules.

It is interesting for me because that is how distributed GLC works:

  • the actor M reacts with the actor R
  • after interaction both molecules may change, the one which belongs to the actor M and the one which belongs to the actor R,
  • but also the actors adjacencies may change as well, due to the reductions involving the reaction between M and R (this corresponds to the receptor activation)
  • which triggers other interactions between GLC actors.

 

Information theory, on the other side, concerns a sender, a channel and a receiver. The sender sends messages through the channel to the receiver.

Completely different frames.

One may, of course, partially ignore the mechanism (signal transduction) and look instead at the environment as a sender, to the cell as a receiver and to the cell’s membrane as a channel (just an example).

But sender, channel and receiver look (to me) as mind constructs which are useful for the human trying to make a sense of what is happening, from outside. What is happening though,  is signal transduction.

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