So, it's been really exciting to be an astrobiologist nowadays
because astrobiology is starting to intersect a lot of other fields
that care very deeply about understanding life -
from the perspective of thinking about more general principles.
And, one of those fields is the artificial life field,
which has been exploring fundamental properties of life
and evolving systems for a number of decades,
and has made a lot of progress in computational models
of living processes that are starting to be able to be used for thinking
about problems relevant to astrobiology.
So, I'm going to just talk about a little bit of...
where artificial life comes into providing some new insights
into what biology might be,
and how we might think about life
as a broader class of phenomena from this astrobiological perspective -
that we want to understand life, not just on Earth,
but life as it might exist anywhere.
And, one of the things that I always find really intriguing -
being trained in physics - is that biology seems to necessitate
a different kind of perspective on how we should think about
the laws of nature, how we should think about...
dynamical systems.
And, one of the things that's really a pretty interesting contrast
between physics and biology is that - in physics, when we model systems,
we always talk about like the initial state.
Like, you could talk of the initial state of the universe
or initial state of the solar system.
And then, you have some fixed law of motion,
like Newton's law of gravitation, or we could take Einstein's theory.
And then, we can evolve our system forward in time
and we can predict the final state.
In principle, we should be able to do that with...
perfect prediction power if we had, you know,
big enough supercomputers and things.
But, there's nothing about the laws of motion that changes in time.
So, Newton's law doesn't change -
it's just the states that evolve forward in time.
But, in biology, we have this really interesting case
where we have an initial state, like that last universal common ancestor
of life on Earth.
And then, as that system evolves, it changes,
and there's many possible final states.
So, even though we started from sort of a...
shared cellular architecture and early history of life,
because of the interaction of life and its environment
and the change of information in those systems,
we've ended up with many, many different final states for biology and...
So, I'm an organism that descended
from that last universal common ancestor.
And, so is the bacteria - you know - on the screen...
the computer screen that I'm looking at right now.
There's many final states possible in biology.
And, one of the ways that we can talk about this
is to even talk about the fact that in biology
this - the states themselves -
are not the only thing that's evolving, but the laws are too.
We talk about state dependent rules or state dependent laws in biology,
and this is the idea - that, as an organism evolves,
its genetic information is changing.
And, even as it...
expresses that genetic information,
it can actually dictate its own state.
So, biology has its property of homeostasis
and regulating its own state - that sort of a state control.
And, this kind of like the rules are actually controlling this state,
or the constraints are controlling the state.
So, that seems really fundamentally different than the situation
that we see in physics and how we model physical systems
that aren't living.
And the real story there is that - in biology -
part of the dynamics is the information
and how the information is changing in time.
And so, in the artificial life field,
people like to try to model these emergent properties,
or what's going on in biology,
using really simple systems
that allow us to understand really basic things about life.
One example that is used commonly in the artificial life field
is cellular automata.
And, one of the reasons that people really like those
is because they have really simple local rules,
just like the laws of physics do,
but we see really interesting global patterns emerging.
And so, for example,
this is an elementary cellular automata "Rule 150,"
and you can see here what the pattern is for the rules.
So, if you have three white cells it maps to one white cell.
If you have three black cells, it maps to a black cell.
And then, different patterns of whites and black cells
will either map to a black or a white cell.
So, it's a very simple rule,
but you'll see that there's this really regular pattern that emerges
when you run the dynamics that's not encoded in the rule at all.
So, we talk about that as an emergent property.
And, life has many emergent properties.
So, one question is -
would those emergent properties of life
be explained by the structure of the laws of physics alone,
or do we need additional principles, and do we really need something
like state planet dynamics or information
or any new principles that are uniquely biological
to explain how biology has this sort of many paths
that we observe through the evolutionary process?
And, that's a great question for artificial life.
People have thought about that from many different perspectives
in addition to cellular automata.
But, we'll talk about cellular automata just a little bit more
because they're a really nice simple example.
And so, as I said, this is an example of this idea in physics
of starting with an initial state of fixed law of motion
and evolving to some final state.
The Game of Life is perhaps one of the most famous examples
of using this kind of construction to understand
what emergent properties are and how complexity can emerge
from simple rules.
So, in The Game of Life,
it's actually a two-dimensional cellular automata
as opposed to the one-dimensional one I showed on the previous slide.
And, what you see is, with The Game of Life,
all kinds of emergent patterns appearing -
from things that glide across your screen
that look like little guns shooting things,
to blinkers, to all kinds of different structures,
and they can interact and make more complex structures.
And so, people have actually... there's sort of a cottage industry
of people studying different emergent patterns in The Game of Life,
and under what conditions they emerge,
what their computational capacity is.
So, it's been a really great toy model system to explore this idea
that emergence might... we might be able to talk about
emergent properties from simple rules.
One of my favorite cellular automata
was actually constructed by John von Neumann,
and he was really interested in this idea of self-reproducing machines.
And so, a self-reproducing machine or automata
would be a system that could make a complete reproduction of itself.
And, he was actually really inspired by Alan Turing
and Turing's work on universal computation.
So, Turing had been interested in whether you could build a machine
that can compute any computable function.
And, von Neumann asked the question, inspired by trying to understand life -
so, this is very early work in the artificial life field -
could you build a machine
that could build any possible machine including itself?
And, if it could do that,
then it would be a self-reproducing machine.
But, it would also be a machine that could - in principle -
be capable of open-ended evolution, which is a really important question -
in the artificial life field related to astrobiology -
about the idea of whether or not evolving systems can keep evolving forever.
So, if you had a self-reproducing machine that could build itself,
but not build any arbitrary machine,
it might stall out and not actually be an evolving system.
And so, von Neumann had this condition that it should be able to build anything -
so that the space of all possible things would be completely open,
that it could potentially evolve into, as long as it could maintain the fact
that it could reproduce itself.
And so, he came up with a particular architecture
that's necessary for such a machine.
What he basically came up with is that
you need to have some kind of information content -
the instructions for specifying the design of the machine.
The machine has to be able to read out those instructions to build itself,
and then it has to be able to have something called a "supervisory unit"
that tells it when to copy the instructions
just as instructions, rather than reading them out.
So, the instructions have to have a dual role.
They have to be able to be copied to be able to reproduce the organism,
but they also have to be read out to be able to be executed
to construct the organism.
And, the machine doing the construction is the part that can...
is the machine that can build any possible machine.
And, he called that a "universal constructor."
And, there is a direct analogy
with modern cellular architecture as we understand it,
in that the translation machinery -
ribosomes and all the associated tRNAs and translation machinery -
could be thought of as a universal constructor
that can construct any possible proteins.
So, it's not a universal constructor
in the sense that it can make any possible object,
but it is a universal constructor in the sense
that it can produce any possible protein.
And, the instruction tape is DNA,
which gets read out by the cell, but also gets blindly copied
by the cell at other stages in cellular function.
So, it does seem to be the case
that this abstract idea from artificial life -
von Neumann's idea of the self-reproducing automata -
actually maps to some of the function that we see in biology.
And so, this was a case where a cellular automata theory
actually predicted some of the logical architecture of modern organisms.
And so, one of the things that's really interesting about von Neumann's idea
was that he had envisioned the possibility of a machine
that could build any possible machine,
which means it could do any possible transformation on physical matter.
And, most cellular automata actually can't do that.
So, if you look at cellular automata and you evolve them forward in time -
in the way that we do, where we have an initial condition
and the cellular automata rule is fixed for all time -
not every state transformation is possible.
So, you can't move from every state to every other state.
But, there is this idea that's implicit in von Neumann's theory
for biological evolution - from this artificial life perspective -
of physical universality, which is the ability to implement
any transformation on any finite region.
The first physical universal cellular automata
was actually just realized recently by Luke Schaeffer...
and he actually demonstrated
that it was possible to construct such a thing.
And, he did so within this sort of traditional physics paradigm,
where he started with an initial state and evolved the system
according to a fixed rule, and the physical universality
comes about by programming the initial state.
Now if you're thinking about things like biological evolution,
then we want to think about biological systems
in this kind of very abstract way inspired by artificial life.
And, think about von Neumann's theory
and what it's really telling us about biology,
one of the things we might hope for is that biology
would actually be capable of performing any arbitrary transformation.
And, a good example of that is modern technology.
So, I think actually modern technology is a better approximation
to a universal constructor than an interior of a cell,
in the sense that technology enables lots of transformations to be possible.
So, for example, we can launch satellites into space.
And, that's not a transformation that would be able to be happening -
we wouldn't be... our planet wouldn't be anti-accreting -
launching things into planetary orbit without having technology.
So, it does allow transformations and biology seems to do this in general.
If you think about metabolism... allows chemical transformations
that seem thermodynamically impossible.
So, if you wanted to talk about those kind of properties
from this cellular automata perspective, what you really would like
is to be able to build a cellular automata
that can perform any arbitrary transformation
and has this kind of inspiration from biology.
So, we've been kind of playing around with those in my group
and this is just sort of an example of...
an artificial life approach to astrobiology.
Thinking about cellular automata with state-dependent laws...
So, the idea here is that we go back to that difference
that we were observing between physics and biology,
and think about the fact that life seems to have this property
where the rules and the states are very tightly coupled.
So... the expression of my genetic information
determines the state of the cells in my body.
My mental state determines something about what I do.
So, if you want to build systems that do that
you can actually build cellular automata with state-dependent laws.
And, you see lots of different rich structures emerging
from these kind of systems, and they do have this property
of physical universality that Schaeffer observed,
but from this very different perspective.
And so, these are just some examples to raise some questions for you
about the kinds of things that we could be thinking about
from more abstract models of life in the artificial life field
to get at more general principles of living systems.
So, we have this idea in mind that information perhaps
might be this unifying principle of life, and that really also comes from
the inspiration of the artificial life field -
because von Neumann was really interested in this idea of the instruction,
the information content being what's specifying the design of the machine,
and that the machine could actually implement those instructions.
And so, in some sense, what he's talking about
is an algorithmic process existing in nature
is necessary to have open-ended evolving systems.
And so, we really don't understand the basic physical principles of that.
And so, one of the things I think is incredibly exciting
about working across the field of artificial life in astrobiology
is that artificial life models have traditionally been these very abstract,
cellular automata type models, or there's other things - like Avida -
that are these digital systems that we program into computers
and we study their properties and they tell us some things
about emergent properties or how systems can evolve.
But, astrobiology affords the opportunity of starting to think about
those kind of things as chemically embodied systems,
and how do we think about the fact that the origin of life transition
actually did happen - these properties emerged
in the natural world from chemistry.
And so, that's really the challenge for astrobiology moving ahead...
is to take the abstract ideas from artificial life
and turn them into quantitative science for astrobiology to build new theories
of what we think life is, and how the transition
from simple molecules to something that has the sophisticated logical
and informational architecture of something
like a von Neumann machine actually emerged on our planet.
And, what does that actually mean in the broadest sense?
And, what are the kind of classes of phenomena
that we might see in the world
that could be inspired by that understanding...
i.e. can we find aliens?
And so, that's really a great thing to think about.