43 research outputs found
Interoceptive robustness through environment-mediated morphological development
Typically, AI researchers and roboticists try to realize intelligent behavior
in machines by tuning parameters of a predefined structure (body plan and/or
neural network architecture) using evolutionary or learning algorithms. Another
but not unrelated longstanding property of these systems is their brittleness
to slight aberrations, as highlighted by the growing deep learning literature
on adversarial examples. Here we show robustness can be achieved by evolving
the geometry of soft robots, their control systems, and how their material
properties develop in response to one particular interoceptive stimulus
(engineering stress) during their lifetimes. By doing so we realized robots
that were equally fit but more robust to extreme material defects (such as
might occur during fabrication or by damage thereafter) than robots that did
not develop during their lifetimes, or developed in response to a different
interoceptive stimulus (pressure). This suggests that the interplay between
changes in the containing systems of agents (body plan and/or neural
architecture) at different temporal scales (evolutionary and developmental)
along different modalities (geometry, material properties, synaptic weights)
and in response to different signals (interoceptive and external perception)
all dictate those agents' abilities to evolve or learn capable and robust
strategies
Synchronization in Music Group Playing
- electronic proceedings available at http://cmr.soc.plymouth.ac.uk/cmmr2015/proceedings.pdf-- paper proceedings published by Springer in the LNCS series, in 2016- the article win the best student presentationInternational audienceIn this project, we created an agent-based model of music group playing under four di↵erent interaction mechanisms. Based on real music data, added randomness and simplifying assumptions, we examine how agents synchronize and deviate from the original score. We find that while music can make synchronization complex, it also helps reducing the total deviation. By studying the simulation process, several conclusions on the relationship between di↵erent growing speeds of total deviations and di↵erent interaction schemes are drawn. With interpretation from a musical point of view, we find that, in a music ensemble, listening to neighbors helps the players end up in sync. However, if people do not listen carefully enough, the deviation becomes larger than when people do not listen at all. On the issue of whom one should listen to, the results show no significant di↵erences between listening to the immediate neighbors and to the whole group. Finally, we also observe that large deviations can be reduced by making the musicians move while playing
Artificial Neurogenesis: An Introduction and Selective Review
International audienceIn this introduction and review—like in the book which follows—we explore the hypothesis that adaptive growth is a means of producing brain-like machines. The emulation of neural development can incorporate desirable characteristics of natural neural systems into engineered designs. The introduction begins with a review of neural development and neural models. Next, artificial development— the use of a developmentally-inspired stage in engineering design—is introduced. Several strategies for performing this " meta-design " for artificial neural systems are reviewed. This work is divided into three main categories: bio-inspired representations ; developmental systems; and epigenetic simulations. Several specific network biases and their benefits to neural network design are identified in these contexts. In particular, several recent studies show a strong synergy, sometimes interchange-ability, between developmental and epigenetic processes—a topic that has remained largely under-explored in the literature
The Evolution of Controller-Free Molecular Motors from Spatial Constraints
Locomotion of robotic and virtual agents is a
challenging task requiring the control of several degrees of
freedom as well as the coordination of multiple subsystems.
Traditionally, it is engineered by top-down design and finetuning
of the agent’s morphology and controller. A relatively
recent trend in fields such as evolutionary robotics, computer
animation and artificial life has been the coevolution and mutual
adaptation of the morphology and controller in computational
agent models. However, the controller is generally modeled as a
complex system, often a neural or gene regulatory network. In the
present study, inspired by molecular biology and based on normal
modal analysis, we formulate a behavior-finding framework for
the design of bipedal agents that are able to walk along a
filament and have no explicit control system. Instead, agents
interact with their environment in a purely reactive way. A simple
mutation operator, based on physical relaxation, is used to drive
the evolutionary search. Results show that gait patterns can be
evolutionarily engineered from the spatial interaction between
precisely tuned morphologies and the environment.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech
Complex and Diverse Morphologies Can Develop from a Minimal Genomic Model
While development plays a critical role in the emergence
of diversity, its mechanical and chemical actions are considered
to be inextricably correlated with genetic control. Since
in most extant species the complex growth from zygote to
adult organism is orchestrated by a complex gene regulatory
network (GRN), the prevalent view is that the evolution
of diverse morphologies must result from the evolution
of diverse GRN topologies. By contrast, this work focuses
on the unique e ect of developmental processes through an
abstract model of self-regulated structure without genetic
regulation|only modulation of initial conditions. Here,
morphologies are generated by a simple evolutionary algorithm
searching for the longest instances of unfolding dynamics
based on tensegrity graphs. The usual regulatory
function of the genome is taken over by physical constraints
in the graphs, making morphological diversity a pure product
of structural complexi cation. By highlighting the potential
of structural development, our model is relevant to
both "structuralist" biological models and bio-inspired systems
engineering.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech
Evolution of Heterogeneous Cellular Automata in Fluctuating Environments
The importance of environmental fluctuations in the evolution of living organisms by natural selection has been widely
noted by biologists and linked to many important characteristics of life such as modularity, plasticity, genotype size, mutation rate, learning, or epigenetic adaptations. In artificial-life simulations, however, environmental fluctuations are usually seen as a nuisance rather than an essential characteristic of evolution. HetCA is a heterogeneous cellular automata characterized by its ability to generate open-ended long-term evolution and “evolutionary progress”. In this paper, we propose to measure the impact of different types of environmental fluctuations in HetCA. Our results indicate that environmental changes induce mechanisms analogous to epigenetic adaptation or multilevel selection. This is particularly prevalent in two of the tested fluctuation schemes, which involve a round-robin inhibition of certain cell types, where phenotypic selection seems to occur.Funding for this work was provided by the Science Foundation Ireland and the ERC Advanced Grant EPNet #340828.
Some of the simulations were run on the MareNostrum supercomputer of the Barcelona Supercomputing Center.Postprint (author's final draft
Embryomorphic Engineering: Emergent innovation through evolutionary development
Embryomorphic Engineering, a particular instance of Morpho-genetic Engineering, takes its inspiration directly from biological development
to create new hardware, software or network architectures by decentralized self-assembly of elementary agents. At its core, it combines three key principles of multicellular embryogenesis: chemical gradient di usion (providing
positional information to the agents), gene regulatory networks (triggering their diferentiation into types, thus patterning), and cell division (creating
structural constraints, thus reshaping). This chapter illustrates the potential
of Embryomorphic Engineering in di erent spaces: 2D/3D physical swarms,
which can nd applications in collective robotics, synthetic biology or nan-
otechnology; and nD graph topologies, which can nd applications in dis-
tributed software and peer-to-peer techno-social networks. In all cases, the
speci c genotype shared by all the agents makes the phenotype's complex
architecture and function modular, programmable and reproducible
Computational modelling unveils how epiblast remodelling and positioning rely on trophectoderm morphogenesis during mouse implantation.
Understanding the processes by which the mammalian embryo implants in the maternal uterus is a long-standing challenge in embryology. New insights into this morphogenetic event could be of great importance in helping, for example, to reduce human infertility. During implantation the blastocyst, composed of epiblast, trophectoderm and primitive endoderm, undergoes significant remodelling from an oval ball to an egg cylinder. A main feature of this transformation is symmetry breaking and reshaping of the epiblast into a "cup". Based on previous studies, we hypothesise that this event is the result of mechanical constraints originating from the trophectoderm, which is also significantly transformed during this process. In order to investigate this hypothesis we propose MG# (MechanoGenetic Sharp), an original computational model of biomechanics able to reproduce key cell shape changes and tissue level behaviours in silico. With this model, we simulate epiblast and trophectoderm morphogenesis during implantation. First, our results uphold experimental findings that repulsion at the apical surface of the epiblast is essential to drive lumenogenesis. Then, we provide new theoretical evidence that trophectoderm morphogenesis indeed can dictate the cup shape of the epiblast and fosters its movement towards the uterine tissue. Our results offer novel mechanical insights into mouse peri-implantation and highlight the usefulness of agent-based modelling methods in the study of embryogenesis
Quantification of cell behaviors and computational modelling show that cell directional behaviors drive zebrafish pectoral fin morphogenesis
Motivation: Understanding the mechanisms by which the zebrafish pectoral fin develops is expected to produce insights on how vertebrate limbs grow from a 2D cell layer to a 3D structure. Two mechanisms have been proposed to drive limb morphogenesis in tetrapods: a growth-based morphogenesis with a higher proliferation rate at the distal tip of the limb bud than at the proximal side, and directed cell behaviors that include elongation, division and migration in a nonrandom manner. Based on quantitative experimental biological data at the level of individual cells in the whole developing organ, we test the conditions for the dynamics of pectoral fin early morphogenesis. Results: We found that during the development of the zebrafish pectoral fin, cells have a preferential elongation axis that gradually aligns along the proximodistal axis (PD) of the organ. Based on these quantitative observations, we build a center-based cell model enhanced with a polarity term and cell proliferation to simulate fin growth. Our simulations resulted in 3D fins similar in shape to the observed ones, suggesting that the existence of a preferential axis of cell polarization is essential to drive fin morphogenesis in zebrafish, as observed in the development of limbs in the mouse, but distal tip-based expansion is not. Availability: Upon publication, biological data will be available at http://bioemergences.eu/modelingFin, and source code at https://github.com/guijoe/MaSoFin. Contact: [email protected], [email protected] or [email protected] Supplementary information: Supplementary data are included in this manuscript
Gardening Cyber-Physical Systems
cote interne IRCAM: Stepney12aNational audienceToday’s artefacts, from small devices to buildings and cities, are, or are becoming, cyber-physical socio-technical systems, with tightly interwoven material and computational parts. Currently, we have to la- boriously build such systems, component by component, and the results are often difficult to maintain, adapt, and reconfigure. Even “soft”ware is brittle and non-trivial to adapt and change. If we look to nature, how- ever, large complex organisms grow, adapt to their environment, and repair themselves when damaged. In this position paper, we present Gro-CyPhy, an unconventional computational framework for growing cyber-physical systems from com- putational seeds, and gardening the growing systems, in order to adapt them to specific needs. The Gro-CyPhy architecture comprises: a Seed Factory, a process for designing specific computational seeds to meet cyber-physical system requirements; a Growth Engine, providing the computational processes that grow seeds in simulation; and a Computational Garden, where mul- tiple seeds can be planted and grown in concert, and where a high-level gardener can shape them into complex cyber-physical systems. We outline how the Gro-CyPhy architecture might be applied to a significant exemplar application: a (simulated) skyscraper, comprising several mutually interdependent physical and virtual subsystems, such as the shell of exterior and interior walls, electrical power and data net- works, plumbing and rain-water harvesting, heating and air-conditioning systems, and building management control systems