Olivier Michel

A review of morphogenetic engineering

Generally, phenomena of spontaneous pattern formation are random and repetitive, whereas elaborate devices are the deterministic product of human design. Yet, biological organisms and collective insect constructions are exceptional examples of complex systems (CS) that are both architectured and self-organized. Can we understand their precise self-formation capabilities and integrate them with technological planning? Can physical systems be endowed with information, or informational systems be embedded in physics, to create autonomous morphologies and functions? To answer these questions, we have launched in 2009, and developed through a series of workshops and a collective book, a new field of research called morphogenetic engineering. It is the first initiative of its kind to rally and promote models and implementations of complex self-architecturing systems. Particular emphasis is set on the programmability and computational abilities of self-organization, properties that are often underappreciated in CS science—while, conversely, the benefits of self-organization are often underappreciated in engineering methodologies. [This paper is an extended version of Doursat, Sayama and Michel (2012b) (Chapter 1, in Doursat R etxa0al. (eds.) Morphogenetic engineering: toward programmable complex systems. Understanding complex systems. Springer, 2012a).]

Group-Based Fields

This paper reports the preliminary work on extending the concept of collection in 81/2. 81/2 is a declarative language that allows the functional definition of streams and collections [1, 2]. In this paper, we focus our interest on a high-level programming abstraction which extends the concept of collection in 81/2. The new construct is based on an algebra of index set, called shape, and an extension of the array type, the field type. The rest of this paper has the following structure. Section 2 gives some background on collections and arrays. Some shortcomings of data-parallel arrays are sketched. Section 3 describes the 81/2 answers to the previous problem and introduces group-based shapes and fields. Section 4 is devoted to the shape algebra. Section 5 introduces the main field operations and field definitions. Section 6 sketches the implementation. Related and future works are discussed in the last section.

Declarative mesh subdivision using topological rewriting in MGS

Mesh subdivision algorithms are usually specified informally using graphical schemes defining local mesh refinements. These algorithms are then implemented efficiently in an imperative framework. The implementation is cumbersome and implies some tricky indices management. Smith et al. (2004) asks the question of the declarative programming of such algorithms in an index-free way. In this paper, we positively answer this question by presenting a rewriting framework where mesh refinements are described by simple rules. This framework is based on a notion of topological chain rewriting. Topological chains generalize the notion of labeled graph to higher dimensional objects. This framework has been implemented in the domain specific language MGS. The same generic approach has been used to implement Loop as well as Butterfly, Catmull-Clark and Kobbelt subdivision schemes.

Rule-based programming for integrative biological modeling

Systems biology aims at integrating processes at various time and spatial scales into a single and coherent formal description to allow computer modeling. In this context, we focus on rule-based modeling and its integration in the domain-specific language MGS. Through the notions of topological collections and transformations, MGS allows the modeling of biological processes at various levels of description. We validate our approach through the description of various models of the genetic switch of the λ phage, from a very simple biochemical description of the process to an individual-based model on a Delaunay graph topology. This approach is a first step into providing the requirements for the emerging field of spatial systems biology which integrates spatial properties into systems biology.

Design and implementation of 812: A declarative data-parallel language

In this article we advocate a declarative approach to data-parallelism to provide both parallelism expressiveness and efficient execution of data intensive applications. 812, an experimental language combining features of collection and stream oriented languages in a declarative framework, is presented. A new structure, the web, allows the programmer to write programmes as mathematical expressions and to implicitly express data and control parallelism. The first part of this paper proposes a classification of the various expressions of parallelism in programming languages. We show that hybrid execution models combining both data and control parallelism are possible and necessary to get an effective speedup. We sketch the advantage of the declarative style with respect to parallelism expression (application side) and exploitation (compiler side). In the second part we describe the 812 language and the concepts of collection, stream and web. A web is a multi-dimensional object that represents the successive values of a structured set of variables. Some 812 programmes are given to show the relevance of the web data structure for simulation applications (a resolution of O.D.P.E. and a simulation in artificial life). Examples of 812 programmes, involving the dynamic creation and destruction of webs, are also given. Such programmes are necessary for simulations of growing systems. In the third part, the implementation of a compiler restricted to the static part of the language is described. We focus on the process of web equations compilation towards a virtual SIMD machine. We also present the clock calculus, the scheduling inference and the distribution of the computations among the processing elements of a parallel computer.

Morphogenetic Engineering: Reconciling Self-Organization and Architecture

Generally, phenomena of spontaneous pattern formation are random and repetitive, whereas elaborate devices are the deterministic product of human design. Yet, biological organisms and collective insect constructions are exceptional examples of complex systems that are both architectured and self-organized. Can we understand their precise self-formation capabilities and integrate them with technological planning? Can physical systems be endowed with information, or informational systems be embedded in physics, to create autonomous morphologies and functions? This book is the first initiative of its kind toward establishing a new field of research, Morphogenetic Engineering, to explore the modeling and implementation of “self-architecturing” systems. Particular emphasis is set on the programmability and computational abilities of self-organization, properties that are often underappreciated in complex systems science—while, conversely, the benefits of self-organization are often underappreciated in engineering methodologies.

Refounding of the activity concept? Towards a federative paradigm for modeling and simulation

Currently, the widely used notion of activity is increasingly present in computer science. However, because this notion is used in specific contexts, it becomes vague. Here, the notion of activity is scrutinized in various contexts and, accordingly, put in perspective. It is discussed through four scientific disciplines: computer science, biology, economics, and epistemology. The definition of activity usually used in simulation is extended to new qualitative and quantitative definitions. In computer science, biology and economics disciplines, the new simulation activity definition is first applied critically. Then, activity is discussed generally. In epistemology, activity is discussed, in a prospective way, as a possible framework in models of human beliefs and knowledge.

Spatial Computing: Distributed Systems That Take Advantage of Our Geometric World

The modeling and control of systems composed of many computational devices is a perennial problem. This problem is growing more acute as the number and density of computing devices continues to rise rapidly. At the macro-scale, the number of computers per person continues to shoot upwards—from traditional PCs and cell-phones to appliances and consumer products to sensor networks and unmanned vehicles— and better and more pervasive networking binds them into larger aggregates. At the micro-scale, the number of devices that can be packed onto a chip continues to climb, and emerging platforms in areas such as nanotechnology and synthetic biology offer the potential to cheaply create systems of billions or trillions of semi-reliable devices. This trend even extends into the natural world, as we learn more about the complex computations carried out by aggregates of living organisms, such as the cells comprising an organism or a biofilm. In recent years, spatial computing has emerged as a promising approach to the modeling and control of these sorts of aggregate systems. The basic insight of spatial computing is simple: when the density of computing devices is high, there is a close relationship between the structure of the network of devices and the geometry of the space through which they are distributed. Put more formally: a spatial computer is any aggregate of devices in which the difficulty of moving information between any two devices is strongly dependent on the distance between them, and the functional goals of the system are generally defined in terms of the system’s spatial structure. This insight gives power in two ways: first, geometric models often enable elegant solutions to problems of robustness, adaptability, scalability, and coordination. Second, the common spatial model unites problems across a wide variety of domains, allowing results to be transferred between them.

Computation and Visualization of Musical Structures in Chord-Based Simplicial Complexes

We represent chord collections by simplicial complexes. A temporal organization of the chords corresponds to a path in the complex. A set of n-note chords equivalent up to transposition and inversion is represented by a complex related by its 1-skeleton to a generalized Tonnetz. Complexes are computed with MGS, a spatial computing language, and analyzed and visualized in Hexachord, a computer-aided music analysis environment. We introduce the notion of compliance, a measure of the ability of a chord-based simplicial complex to represent a musical object compactly. Some examples illustrate the use of this notion to characterize musical pieces and styles.

Activity regions for the specification of discrete event systems

The common view on modeling and simulation of dynamic systems is to focus on the specification of the state of the system and its transition function. Although some interesting challenges remain to efficiently and elegantly support this view, we consider in this paper that this problem is solved. Instead, we propose here to focus on a new point of view on dynamic system specifications: the activity exhibited by their discrete event simulation. We believe that such a viewpoint introduces a new way for analyzing, modeling and simulating systems. We first start with the definition of the key notion of activity for the specification of a specific class of dynamic system, namely discrete event systems. Then, we refine this notion to characterize activity regions in time, in space, in states and in hierarchical component-based models. Examples are given to illustrate and stress the importance of this notion.