Sometimes the findings made in molecular biology seem like countless, tiny pieces of an enormous jigsaw puzzle: some of them we have managed to connect together, forming little islands of knowledge, but they are overall so far apart that we cannot make out what the entire picture is supposed to look like.
The analytic and reductionist approach has brought a lot of success to modern biology, especially at molecular level, chopping things into ever smaller slices. Still, I have to confess that I often feel like I am sinking in a pit of despair smothered by terabytes of scientific data that has been produced by countless research groups doing nothing more than just piling up and sitting stored somewhere without anyone truly knowing what it means. The hot thing to do nowadays is to produce “big data” and obtain an ocean of information on everything, from a single cell to a cancerous tumor.
However, is this really getting us any closer to actually understanding the biology of it? The current state of affairs with science seems to call for an urgent unification and interpretation of all the information produced in the last few decades.
This is not the only approach, and people have been venturing into alternative pursues for the clarification of these biological mysteries for an embarrassingly long time already; the thing is, not many people seem to really care about what they want to say.
In 1987, Chris Langton and a small group of hardcore computer, philosophy and biology geeks gathered in what came to be the first conference on Artificial Life, a newly emerged discipline that started to produce promising advances on the unraveling of the hidden facts of the nature of life on Earth.
Such achievements included computer programs that reproduced the behavior of flocks and schools of fish, models portraying the emergence and evolution of life, cellular automatons and little virtual organisms that adapted within their simulated ecosystems.
An example of a cellular automaton: CONWAY’S GAME OF LIFE
In 1970, mathematician John Horton Conway devised a game called “Life”. Such game could be played in a simple checkered board (like a chess board) using a few pieces. Each square on the board symbolizes a cell and can be either “full” (when a piece is in it) or “empty”.
In the board, each cell has eight neighboring cells (the surrounding squares on the board). The game starts by placing the pieces in the squares in a chosen initial position; then, the game progresses step by step, with each individual step determining the state of the next one by using the following rules:
1) An empty cell will become full if three of its neighbors are full.
2) A full cell remains so if two or three of its neighbors are full, otherwise it becomes empty.
In this way, the state of the neighboring cells is accounted for each cell, and the rules stated above determine what the state of each cell will be in the next generation. By doing this repeatedly, interesting patterns begin to emerge, depending on the initial position chosen; sometimes the game dies down quickly, and sometimes the game fluctuates or stagnates due to cells being isolated and clustered together.
In fact lots of crazy and unexpected patterns obtained by playing this game have been documented, some of them are pretty impressive and really look like a living system. People actually became addicted to playing this game in computers (mind you, it was the late 70's/early 80's). You can see some really cool examples of these life-like behaviors here.
One of the most powerful tools that artificial life provides is its holistic perspective and wholesome way of solving problems. One of the biggest goals of artificial life is to achieve the synthesis of life, or at the very least achieving a simulation that is very close in function to a living system.
However, to successfully accomplish this, artificial life must make use of the immense wealth of data about living organisms that modern biology has managed to accrue until now. Before we study the interactions and relations between the different parts of the whole, we still need to know the components and the individual functioning of each part. Hence, the knowledge obtained in a highly specialized and reductionist way is still incredibly valuable! It will become building blocks for more complex and sophisticated systems.
Of course, we also need to have at least a general idea of what life is in order to be able to synthesize it in the computer. One of the advantages offered by artificial life is the lack of prejudice about the way in which life can be represented; many people argue about whether such computer-based entities can truly be considered “alive”, or if life can be built with different materials to those that form the living forms we are already familiar with. This is the point where proponents of Artificial Life usually fall into one of two factions:
- The “hard” one, that claims that the organisms generated in the computer are indeed autonomous living beings subject to evolution (according to this posture, Conway’s game of life could be considered a legit living system), and
- The “soft” one –which we could say it’s the most politically correct one and won’t cause anyone’s monocle to be dropped in outrage– which supports that such computer creations are highly sophisticated simulations of the real phenomenon that is life.
Going even further, one could argue that depending on the level we look at, things can appear more or less alive. All living beings are composed by the same atoms, which in turn are composed by electrons and particles in constant agitation, therefore in a sense we could say that true death would be the complete cessation of such movement– a radical notion already proposed by Mexican biologist Alfonso Herrera in 1904.
Building into this idea is the concept of autopoiesis (literally “autoproduction”), which was a property proposed by biologist Humberto Maturana as the fundamental distinction between the living and the non-living. Autopoiesis refers to the network of self-organization and production within a living unit (a cell, for example), in which the products of the processes within the network help to maintain it while simultaneously being part of it.
Working with the concept of autopoiesis in computer simulations has allowed to cast some light into other interesting philosophical problems about the nature of life, one of them being emergence.
Emergence the fascinating property of life that makes the whole into much more than the sum of its parts. The apparent contradiction regarding emergence lies in that emergent phenomena in living organisms are at the same time autonomous and dependent from the basic processes that conform them. In other words, how can we consider something as autonomous, when it is dependent on its basic phenomena or processes?
Artificial life can help us find an answer for this question. In it, we can see that such emergent properties do not arise in an unexplained or metaphysical way, but as a result of countless interactions on a “micro-level”, the consequences of which reverberate into the “macro-level” or the observable level, exhibiting behaviors that were not expected when only taking into account the initial components.
From the point of view of artificial life, then, a property that is considered as emergent in a system must be a result of the dynamic interactions within such system in a micro-level, as the result of processes like iteration and aggregation of components. In this way, we can start taking a peek behind the veil of how life originates!
Fun facts about the history of artificial life:
Through decades of research and speculation by some of the most imaginative minds in science, the development of artificial life systems has produced some truly fantastic episodes:
- There are several examples of people attempting to "animate" machines dating back as far as the 18th century. One of these examples is the mechanical duck created by some Jacques de Vaucanson in 1735. The mechanical animal used to tour around like an attraction, and reports state that it moved in a way that conveyed autonomy, and more surprisingly it was capable of eating food and digesting it –all the way to the last step!
- In 1980, a very out-of-the-box team sponsored by NASA came up with the idea of producing self-replicating lunar factories that would be used for space colonization and exploration of mineral resources within the solar system and beyond. The idea was that such systems would be able to produce their own components, copy themselves and proliferate. An extensive discussion on the project was done (including the potential threat to humankind of having such "living" factories invading the universe), but the project was never realized.
- Computer-generated swarm intelligence has been applied not only for scientific purposes, but also for entertainment. A famous example of this, was the use of such algorithms to animate the computer-generated armies for the war scenes in the Lord of the Rings films!
Irime
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References:
- Emmeche, Claus. 1994, The garden in the machine: the emerging science of artificial life. Princeton University Press.
- Levy, Steven. 1992. Artificial Life: The quest for a new creation. Penguin Books.
- The Ontological Status of Artificial Life
I like to wonder about the nature of autopoiesis itself from time to time. How some positive feedback loops give rise to something new while some end in "death". The limiting rate would appear to be energy efficiency from the medium but some systems while inefficient, can support themselves by pure signaling to higher orders of complexity that apport bigger sources of energy. It all looks to me, quite similar to games and gamification.
@ertwro, it really looks like it, isn't it?
For me AL really made it more clear that when it comes down to interaction and selection of pathways, endless processes of repetition and iteration play a big part. I can see, for example, molecules like proteins interacting with each other in this way, triggering chain reactions that could have productive outcomes (and therefore remain in the pool of selected paths, "alive"), or do nothing and become a dead end.
I have to say that I need to read more of Maturana and Varela's work on this; re-reading the books I listed above re-sparked my interest in the topic!
I don't recall the source but I believe to have heard that you can use the game of life on a small lattice to program a game of life on a larger lattice.
Yo dawg, we heard you like the game of life...
Not sure about this either... but the game is scalable for sure!
I remembered an AL game I played 20+ years ago: https://steemit.com/science/@wentong-syhhae/play-god-create-your-own-lifeforms-experiments-in-artificial-life
Very fascinating.
I am part of the specialiced, reductional cohort (as most scientists are today), but I too see the need to bring together learned details. On the other hand, communication of science gets harder and harder the more specialized we are, as each field has its own sophisticated language.
AL is an interesting approach to solve some of these problems for sure.
@sco, I know what you mean, I also experience it. Every time someone asks me "what is your project about" I try to put it in very simple words; however if they ask further I realize immediately that there are lots of background knowledge that I would need to explain in order for them to grasp the main hypothesis I work with.
I think anything that works on understanding general principles rather than specifics, like AL, can help us make big leaps in the way we understand the biology of things.
Actually, the idea of self-replicating factories can be traced back much earlier than the 1980s: John von Neumann came up with the idea in the 1940s: https://en.wikipedia.org/wiki/Von_Neumann_universal_constructor
(for impatient people) Von Neumann's ideas are discussed at 1:44:
Still, this is a fascinating (and somewhat frightening) idea. Thank you for bringing it up! (resteemed)
That is true! Thank you very much for the video, (and for the resteem!), @wentong-syhhae. It fits really nicely with the topic! Explains the whole concept of self-replicating factories (and its implications) in a very accessible way.
Von Neumann is such a fascinating character, but at the same time he strikes me as a bit of a tragic figure: a man with such an incredible intellect that had so much to offer, so much to do, limited by a premature death sentence set by cancer. In the book by Steven Levy that I cited above you can read about how he was in a desperate race against time (having only months to live from the time of his diagnosis) to try and get as much work done as possible to make his dream ideas come to fruition.
Very interesting post!
Thanks for the research.
Incredible that the humans tried to build these kinds of autonomic machines already in the 18th century.
Honestly I didn't know that.
The human race is just unbelievable.
Indeed! I was also very surprised. As I biologist I was especially intrigued as to how they managed to mimic the "digestion" in that duck... maybe they designed some sort of mini-bioreactor with real bacteria in it?
Thanks for your comment, @infinityroad.
artificial life can be"alive" it's just our perception ...if in the future science will succeed in creating artificial intelligence and your PC will be your best friend you will no longer regard it as one thing....he will become a real person for you ...
This reminds me of the idea behind that movie "Her", or the character Joi from the new Blade Runner film.
I think many of us are just still really rooted in the idea that alive things have to be organic, however faulty that assumption might be!
Wow, it's amazing that a mechanical duck has been created as far as 1735. :o
I often wonder how many of these marvels were just lost in time... thanks for stopping by, @lifenbeauty!
Morning cup of coffee and awesome reading piece. May you have a wonderful day @irime
Thanks for such positive feedback, @gamainvegas!
Great information ...along with well elaborated examples.
Thank you!
thanks for the important info
@resteem
Thanks for the resteem, @nachon!
@irime
As the biology And artificial life
can teach us about the nature of living systems which is mush possible for us.
And the investigative and reductionist approach has conveyed a considerable measure of achievement to present day science, particularly at sub-atomic level, cleaving things into ever littler cuts. All things considered, I need to admit that I regularly feel like I am soaking in a pit of gloom covered by terabytes of logical information that has been delivered by endless research bunches doing simply heaping up and sitting put away some place without anybody really recognizing what it implies. The hot activity these days is to deliver "enormous information" and acquire a sea of data on everything, from a solitary cell to a harmful tumor. Now the possibility have reached here to learn and do anything with research.
Thank you, @irime! This post has inspired me to look up an artificial life game I played over twenty years ago:
https://steemit.com/science/@wentong-syhhae/play-god-create-your-own-lifeforms-experiments-in-artificial-life
what do you think of chemical autopoietic systems?
eg. Pier Luigi Luisi, http://automatos.pbworks.com/f/luisi_autopoiesis.pdf