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I have founded the field of morphogenetic engineering, the first
initiative of its kind to establish a new trend of research exploring
the modeling and implementation of "self-architecturing" systems.
It focuses on the programmability of self-assembling agents,
which is often underappreciated in complex systems science—while,
conversely, the benefits of self-organization are often underappreciated
in systems engineering.
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Classical engineered products (mechanical, electrical, computer,
civil) are generally made of a number of unique, heterogeneous
components assembled in very precise and complicated ways. They are
expected to work as deterministically as possible following the
specifications given by their designers. By contrast, self-organization
in natural systems (physical, biological, ecological, social) often
relies on myriads of identical agents and essentially stochastic
dynamics.
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Abstract modeling and simulation of the fundamental principles of self-patterning
and self-assembly during embryonic development, for exportation to artificial systems
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The spontaneous making of an entire organism from a single cell is
the epitome of a self-organizing and programmable complex
system. Through a precise spatiotemporal interplay of genetic switches
and chemical gradients, an elaborate form is created without explicit
architectural plan or engineering.
Embryomorphic engineering, a methodology I created,
proposes a multi-agent abstraction of these
fundamental morphogenetic mechanisms toward artificial systems.
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A precursor instance of morphogenetic engineering, embryomorphic
engineering proposes an artificial reconstruction of biological
morphogenesis. Inspired by "evo-devo" (see e.g. Kirschner
& Gerhart 2005), it focuses on the causal
and programmable link from genotype to phenotype at these two
levels simultaneously, something needed in many emerging
computational domains.
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A study of functional artificial morphologies through a
model of animated embryomorphic organisms immersed in a virtual 3D environment
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In this work, carried out by my PhD student Carlos Sánchez under the co-supervision of
Taras Kowaliw,
development follows the same principles as the
precursor 2D
model—self-assembly by elastic forces, pattern formation by gradient
propagation and gene expression. In addition here, developed organisms can
generate movement by contracting adhesion links between "muscle" cells, while
other cells have differentiated into "bones" and "joints" to support and articulate
the body’s structure.
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While the task of "meta-designing" laws of artificial development inspired from biology
is already challenging, it only constitutes the first part of the
effort.
Once a self-developing infrastructure is mature, what other computing
and behavioral capabilities can it support?
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The self-assembly of complex but precise network topologies by
programmed attachment: An example of model extending
from
multicellular organisms to graphs
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In this model of autonomous network construction and dynamics,
which I derived from ,
and was in part implemented by MSc students
A. MacDonald &
R. Dordea,
nodes execute the same program in parallel,
communicate and differentiate, while links are dynamically created
and removed based on "ports" and "gradients" that guide nodes to
specific attachment locations. As the network expands, nodes switch
different rules on and off, creating chains, lattices, and other
composite topologies.
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Nodes carry various pairs of attachment ports (X, X') and
corresponding gradient values (x, x'). Node ports can be "free"
(not linked to other ports from other nodes) or "occupied" (linked),
while free ports can be "open" (available for a connection) or
"closed" (disabled). New nodes that just arrived in the system's
space, or nodes that are not yet connected, have both ports open
and gradients set to 0.
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iscpif.fr
