Engineering and Control of Self-Organization

Chair: René Doursat


Artificial complex systems can be created to analyze, model and regulate natural complex systems. Conversely, new and emergent technologies can find inspiration from natural complex systems, whether physical, biological or social. Modeling and simulation are crucial complementary tools in the exploration of complex systems. The recent and fast-growing development of complex systems research in many scientific fields, along with the strong interdisciplinary interactions that it created, was greatly stimulated by the striking advances in computer networks and high-performance calculation. Information and communication technologies represent today a major tool of investigation in complex systems science, often replacing analytic and phenomenological approaches in the study of emergent behavior. In return, information technologies also benefit from complex system research.

The ECSO e-track features innovative cross-disciplinary fields that attempt to solve, at their core, the paradox of “engineering and controlling self-organization” in various ways. For this reason, ECSO researchers often have difficulties finding a home in traditional venues — established conferences or journals, university departments or schools — as they are torn between scientific domains focused on the observation and modeling of natural complex systems (in which they appear too “artificial” and disconnected from “real data”) and engineering domains more interested in top-down design and optimization of reliable “complicated systems” than complexity per se (in which their meta-designs appear too “soft” or “bioinspired” and not sufficiently “proven”).


The ECSO e-track thus purports to be a unifying pole between two big families: complex systems and engineeering, which are traditionally not communicating, yet have witnessed the rise of a new, unofficial intersection populated with numerous original ideas and topics. Reflecting this diversity, it will be featuring invited talks in the following areas:

  • Artificial chemistries
    Lidia Yamamoto, KU Leuven, Belgium

    The field of Artificial Life (ALife) is now firmly established in the scientific world, but it has yet to achieve one of its original goals: an understanding of the emergence of life on Earth. The new field of Artificial Chemistries draws from chemistry, biology, computer science, mathematics, and other disciplines to work toward that goal. For if, as it has been argued, life emerged from primitive, prebiotic forms of self-organization, then studying models of chemical reaction systems could bring ALife closer to understanding the origins of life. In Artificial Chemistries (ACs), the emphasis is on creating new interactions rather than new materials. The results can be found both in the virtual world, in certain multiagent systems, and in the physical world, in new (artificial) reaction systems. [book]

  • Autonomic computing: autonomic management in open multi-objective computing networks
    Ada Diaconescu, Télécom ParisTech, Paris, France

    “Autonomic computing” aims to address the challenge of managing complex computing systems by enabling them to self-administer (e.g. self-configure, -heal, -optimise, -protect, and -adapt). In addition to specific self-management algorithms, autonomic systems that operate in complex competitive environments must also be able to dynamically integrate such algorithms and other computing resources into a coherent whole, in order to adapt to changing objectives and to use available resources opportunistically. This presentation will show how software engineering can facilitate the understanding, development and maintenance of such networked autonomic systems; by offering a structural and methodological foundation that includes generic goal formalisations and reusable integration patterns. [book]

  • Collective construction: automating construction with robot swarms
    Justin Werfel, Harvard University, Cambridge, MA, United States

    Termites build huge, complex structures through the collective actions of millions of independent agents. These natural systems inspire the research area of collective construction, whose goal is to develop autonomous multi-robot systems that build large-scale structures according to user specifications. This presentation will give a brief overview of work in this field, and discuss the design and realization of a system of climbing robots that flexibly build structures using specialized building blocks. Robots act independently under decentralized control, using local information, onboard sensing, and implicit coordination through manipulation of a shared environment. A user can specify a target structure using a high-level representation, and robots follow simple rules that guarantee the correct completion of that structure. [paper]

  • Complex systems engineering: multi-scale collective construction in artificial insects
    Seth Bullock, University of Bristol, United Kingdom

    In many insect species, colonies of individuals collaborate to construct impressive homes. These structures can exhibit functional organisation at many scales despite the limited cognitive capacity of the individual builders. Understanding how these feats of collective construction are achieved could unlock a new design paradigm for human architecture. Here, a series of simulation studies of collective construction in populations of idealised artificial insects is presented. Particular consideration is given to the problem of simultaneously achieving both fine-grained spatial structure and large-scale spatial organisation by combining distal and proximal behavioural mechanisms in the form of pheromone-mediated behaviour and stigmergic building rules. [paper]

  • Decentralized sensor networks
    Matt Duckham, RMIT University, Melbourne, Australia

    Geospatial information has traditionally been stored and processed in physical locations that are unrelated to the actual locations referred to in that information. However, spatial data capture and computing devices are increasingly embedded in geographic space. Technologies like geosensor networks, for example, can be embedded in built and natural environments to capture, compute with, and communicate dynamic geographic information. The challenge is to equip these embedded technologies with the capability to respond directly, “in the network”, to spatiotemporal queries about the rapidly changing environment. This talk introduces the key principles behind computing with dynamic spatiotemporal information “in the network”, what makes such computing environments different from traditional spatial computing, and providing examples of some fundamental algorithms, approaches, and applications of decentralized spatial computing. [book]

  • Evolutionary collective robotics: embodied evolution and lifelong learning
    Nicolas Bredeche, Université Pierre et Marie Curie, Paris, France

    I will present how evolutionary robotics can be used for designing and studying collective (robotic) systems. This talk will cover both evolutionary robotics as an off-line design method (search for a solution, then use it), and as an on-line design method (search for a solution while the robots are already deployed). I will also describe our recent work on environment-driven evolutionary adaptation, i.e. on-line distributed algorithms that can be used to deploy a swarm of robots in open environments, where the tasks to achieve self-sustainability are unknown to the experimenter prior to deployment. Finally, I will discuss how evolutionary robotics for collective systems can be used both for engineering (as a design method) and biology (as a modelling and simulation method). [issue]

  • Guided self-organization: information dynamics of complex computation
    Mikhail Prokopenko, University of Sydney, Australia

    The study of how order is created out of interactions, despite a relentless flow of increasing entropy, is one of the most rewarding scientific experiences. Furthermore, finding ways to guide the processes, which seemingly spontaneously self-organise, towards desirable outcomes is among the most complex engineering tasks. Identifying fundamental principles for Guided Self-Organisation (GSO) would make a profound theoretical and practical contribution with far-reaching implications for both science and engineering. Is it possible to guide the process of self-organisation towards specific patterns and outcomes? Wouldn’t this be self-contradictory? After all, a self-organising process assumes a transition into a more organised form, or towards a more structured functionality, in the absence of centralised control. This talk presents different approaches to resolving this paradox. In doing so, the case studies presented cover a broad range, from celular automata to information cascades in swarms to phase transitions in dynamical systems. [book]

  • Morphogenetic engineering: toward programmable complex systems
    René Doursat, CNRS, Gif-sur-Yvette, France

    Two major types of morphogenetic complex systems can be distinguished: ones that display simple repetitive patterns (spots and stripes) and ones that produce sophisticated functional shapes (bodies and constructions). We are interested here in the latter, since they represent decentralized systems endowed with a modular architecture, which can be observed in biology at every scale (cells, organisms, insect constructions) and also in certain engineered devices of a highly distributed nature (multi-agent software). To describe these architectures without architects, the concept of “morphogenetically architected complex systems” (MACS) allows drawing a link between spontaneously evolved biological and industrial complex systems, while at the same time focusing on structure. From there, we can address the question of (re)taking control of these systems, i.e. guiding or programming them toward more specific and beneficial outcomes. Broadly, this can be achieved in two ways: by instilling more self-organization into computing artefacts (swarm robotics, autonomous networks) and, conversely, by instilling more information technology into self-organizing natural objects (synthetic biology, organ growth). [book]

  • Organic computing
    Christoph von der Malsburg, Frankfurt Institute for Advanced Studies, Germany

    As outlined in Denis Bray’s book “Wetware”, living cells, brains and computers can be seen as vast arrays of switches able to perform purposefully. The term “computing” was originally understood as referring to the deterministic manipulation of symbols under algorithmic (that is, human) control, but by now it has acquired connotations that let it be applied also to the non-deterministic, evolving, self-organizing and learning processes going on in cells and brains and that suggest novel ways to think about the vast signal processing network beginning to endow the globe with a nervous system. I will briefly outline what the fields dealing with cells, brains and computers have in common and how they can profit from the exchange of ideas and methods. [book]

  • Pervasive adaptation: knowledge commons and design contractualism
    Jeremy Pitt, Imperial College, London, United Kingdom

    The convergence of pervasive computing, adaptive systems and big data is creating new range of technological opportunities: new interfaces, new affordances, new signals. It is also creating a new range of social perils, especially those related to privacy and civil liberties, the (so-called) sharing economy, and the commodification of social concepts. In this talk, we discuss a technological readiness and risk assessment inspired by a comparative evaluation against Ira Levin’s dystopian novel “This Perfect Day”, and propose to re-think models of security, privacy, and usability. We also discuss engineering self-organisation in the context of knowledge commons and design contractualism, to ensure that data generators are also the primary beneficiaries. [book]

  • Soft and amorphous robotics: why soft robots are so hard
    John Rieffel, Union College, Schenectady, NY, United States

    Imagine a deformable robot able to squeeze through small apertures to reach a survivor trapped in rubble, or a minimally invasive surgical arm capable of dynamically adapting to multiple roles, from hemostat to syringe. Long the realm of science fiction, recent advances in material science and rapid prototyping offer to bring soft robotics into the real world, opening up an entire new realm of operational capabilities. However, this deformability and adaptability comes at a cost: soft robots by nature have nearly infinite degrees of freedom and high degrees of dynamical coupling, causing them to be necessarily under-actuated and under-controlled. This dynamical complexity precludes the use of conventional robotic control techniques. This survey of the field will discuss some of the challenges and hopes for the future of soft robots. [paper]

  • Spatial computing: from interaction to computation
    Antoine Spicher, Université Paris-Est Créteil, France

    Spatial computing is an emergent field of computer science which explicitly identifies the importance of space in computation at the three levels of hardware, programming and software. In this presentation, we focus on an original programming paradigm inspired by the spatial structure induced by the dynamics of complex systems, namely the topology of interactions. The resulting interaction-based programming language called MGS is used in many areas (especially in integrative and synthetic biology) for the modeling of morphogenetic phenomena. Finally, we show that global/local relationships characteristic of complex systems can also be integrated into this framework by modeling them at different levels of description. [paper]

  • Swarm chemistry: guiding designs of self-organizing swarms
    Hiroki Sayama, Binghamton University, NY, United States

    Self-organization of heterogeneous particle swarms is rich in its dynamics but hard to design in a traditional top-down manner, especially when many types of kinetically distinct particles are involved. In this talk, we discuss how we have been addressing this problem by (1) utilizing and enhancing interactive evolutionary design methods and (2) realizing spontaneous evolution of self organizing swarms within an artificial ecosystem. [web]

  • Synthetic biology: toward a behavior-matching genomic compiler of desired cell functions
    Franck Delaplace, Université Evry Val d’Essonne, France

    The field of synthetic biology is in need of an engineering framework to safely design reliable biological functions de novo. Computer aided design (CAD) should play a central role in this endeavor. Yet, while CAD environments are commonly used in artificial systems engineering, their application to synthetic biology is still in its infancy. Here, we address the challenge of creating a high-level programming language especially suited for CAD in synthetic biology. We propose GUBS (Genomic Unified Behavioral Specification), a language describing the desired behavior of cells, together with a compiler capable of selecting the appropriate genomic components in such a way that the observation of the synthetic biological functions resulting from their assembly matches the programmed behaviors. [paper]

Dates and times to be announced soon.