Self-repair ability of evolved self-assembling systems in cellular automata

Self-repairing systems are those that are able to reconfigure themselves following disruptions to bring them back into a defined normal state. In this paper we explore the self-repair ability of some cellular automata-like systems, which differ from classical cellular automata by the introduction of a local diffusion process inspired by chemical signalling processes in biological development. The update rules in these systems are evolved using genetic programming to self-assemble towards a target pattern. In particular, we demonstrate that once the update rules have been evolved for self-assembly, many of those update rules also provide a self-repair ability without any additional evolutionary process aimed specifically at self-repair

Evolutionary morphogenesis for multi-cellular systems

With a gene required for each phenotypic trait, direct genetic encodings may show poor scalability to increasing phenotype length. Developmental systems may alleviate this problem by providing more efficient indirect genotype to phenotype mappings. A novel classification of multi-cellular developmental systems in evolvable hardware is introduced. It shows a category of developmental systems that up to now has rarely been explored. We argue that this category is where most of the benefits of developmental systems lie (e.g. speed, scalability, robustness, inter-cellular and environmental interactions that allow fault-tolerance or adaptivity). This article describes a very simple genetic encoding and developmental system designed for multi-cellular circuits that belongs to this category. We refer to it as the morphogenetic system. The morphogenetic system is inspired by gene expression and cellular differentiation. It focuses on low computational requirements which allows fast execution and a compact hardware implementation. The morphogenetic system shows better scalability compared to a direct genetic encoding in the evolution of structures of differentiated cells, and its dynamics provides fault-tolerance up to high fault rates. It outperforms a direct genetic encoding when evolving spiking neural networks for pattern recognition and robot navigation. The results obtained with the morphogenetic system indicate that this "minimalist” approach to developmental systems merits further stud

Enaction-Based Artificial Intelligence: Toward Coevolution with Humans in the Loop

This article deals with the links between the enaction paradigm and artificial intelligence. Enaction is considered a metaphor for artificial intelligence, as a number of the notions which it deals with are deemed incompatible with the phenomenal field of the virtual. After explaining this stance, we shall review previous works regarding this issue in terms of artifical life and robotics. We shall focus on the lack of recognition of co-evolution at the heart of these approaches. We propose to explicitly integrate the evolution of the environment into our approach in order to refine the ontogenesis of the artificial system, and to compare it with the enaction paradigm. The growing complexity of the ontogenetic mechanisms to be activated can therefore be compensated by an interactive guidance system emanating from the environment. This proposition does not however resolve that of the relevance of the meaning created by the machine (sense-making). Such reflections lead us to integrate human interaction into this environment in order to construct relevant meaning in terms of participative artificial intelligence. This raises a number of questions with regards to setting up an enactive interaction. The article concludes by exploring a number of issues, thereby enabling us to associate current approaches with the principles of morphogenesis, guidance, the phenomenology of interactions and the use of minimal enactive interfaces in setting up experiments which will deal with the problem of artificial intelligence in a variety of enaction-based ways

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

Fictional Proto-architecture as an Introduction to Biologic Design: Challenging the Concept of Morphogenesis of Neo-architectural Organism

The architecture is based on a dialectical search for new ways of matter representation. We deal with the form of contemporary architecture under two approaches: expression and content. The article examines how mathematical principles based on natural growth can be applied in architectural design to create a dynamic, not static, structure. The dynamic process of the cell and its growth provides the basic structure. The continuity of the domain is exemplified by the impact of the new forms on the society that has already begun to emerge from the obscurity. The paper argues that without a deeper and more receptive connection between geometry and performance from a bio-morphogenetic perspective of complex systems. The experimental design methods are applied both to generate and to evaluate an architecture of the futuristic lines. These methodological frameworks focus on cyclically restated themes in the field of parametrises, which are identified as endemic to architecture: the realization of buildings, of multifunctional volumes and customized per se through a gradual approach of the architectural properties and the exploitation of a "concept construction" integrated as a process, obtained through innovative modelling environments. And so, and the reconstruction of architecture as an organ of nature is demonstrated. The new vanguard of proto architecture describes difficulties and inconsistencies in the relationship between theories and structures, difficulties arising from the very idea of "virtually" itself. It becomes difficult to say that a drawing in cyberspace is an architectural form or just a graph of architectural theory; in the virtual space, there is no difference between the particular structure and the general principle. Therefore, the form is first designed, only after to be constructed. Naturally, it is impossible (theoretically or technically) for design and construction processes to take place simultaneously. Predictably, bio-morphosis leads to multiple forms of expression, defined and transmitted in geometric terms. Doi: 10.28991/esj-2020-01248 Full Text: PD

Vector Field Embryogeny

We present a novel approach toward evolving artificial embryogenies, which omits the graph representation of gene regulatory networks and directly shapes the dynamics of a system, i.e., its phase space. We show the feasibility of the approach by evolving cellular differentiation, a basic feature of both biological and artificial development. We demonstrate how a spatial hierarchy formulation can be integrated into the framework and investigate the evolution of a hierarchical system. Finally, we show how the framework allows the investigation of allometry, a biological phenomenon, and its role for evolution. We find that direct evolution of allometric change, i.e., the evolutionary adaptation of the speed of system states on transient trajectories in phase space, is advantageous for a cellular differentiation task

Artificial Gene Regulatory Network and Spatial Computation: A Case Study

International audienceThis paper explores temporal and spatial dynamics of a population of Genetic Regulatory Networks (GRN). In order to so, a GRN model is spatially distributed to solve a multi-cellular Artificial Embryogeny problem, and Evolutionary Computation is used to optimize the developmental sequences. An in-depth analysis is provided and show that such a population of GRN display strong spatial synchronization as well as various kind of behavioral patterns, ranging from smooth diffusion to abrupt transition patterns

Artificial Gene Regulatory Networks and Spatial Computation: A Case Study

International audienceThis paper explores temporal and spatial dynamics of a population of Genetic Regulatory Networks (GRN). In order to so, a GRN model is spatially distributed to solve a multi-cellular Artificial Embryogeny problem, and Evolutionary Computation is used to optimize the developmental sequences. An in-depth analysis is provided and show that such a population of GRN display strong spatial synchronization as well as various kind of behavioral patterns, ranging from smooth diffusion to abrupt transition patterns