Taras Kowaliw

French National Centre for Scientific Research | CNRS · ISC-PIF

Synthetic biology is an emerging scientific field that promotes the standardized manufacturing of biological components without natural equivalents. Its goal is to create artificial living systems that can meet various needs in health care or energy domains. While most works are focused on the individual bacterium as a chemical reactor, our project...

We study properties of Linear Genetic Programming (LGP) through several regression and classification benchmarks. In each problem, we decompose the results into bias and variance components, and explore the effect of varying certain key parameters on the overall error and its decomposed contributions. These parameters are the maximum program size,...

In 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 beginswith a review of neural development and neu...

We show how a biologically inspired model of multicellular development combined with a simulated evolutionary process can be used to design the morphologies and controllers of soft-bodied virtual animats. An animat’s morphology is the result of a developmental process that starts from a single cell and goes through many cell divisions, during which...

In this work we study open-ended evolution through the analysis of a new model, HetCA, for "heterogeneous cellular automata". Striving for simplicity, HetCA is based on classi-cal two-dimensional CA, but differs from them in several key ways: cells include properties of "age", "decay", and "quies-cence"; cells utilize a heterogeneous transition fun...

We propose an evolutionary feature creator (EFC) to explore a non-linear and offline method for generating features in image recognition tasks. Our model aims at extracting low-level features automatically when provided with an arbitrary image database. In this work, we are concerned with the addition of algorithmic depth to a genetic programming (...

In this chapter, we argue that artificial development is an appropriate means of approaching complex systems engineering. Artificial development works via the inclusion of mechanisms that enhance the evolvability of a design space. Two of these mechanisms, regularities and adaptive feedback with the environment, are discussed. We concentrate on the...

Embryomorphic Engineering, a particular instance of Morphogenetic Engineering, takes its inspiration directly from biological development to create new robotic, software or network architectures by decentralized self-assembly of elementary agents. At its core, it combines three key principles of multicellular embryogenesis: chemical gradient diffus...

Today'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 laboriously build such systems, component by component, and the results are often difficult to maintain, adapt, and reconfigure. Even "soft" ware...

We use a new measure of creativity as a guide in an interactive evolutionary art task and tie the results to natural language usage of the term “creative.” Following previous work, we explore a tractable definition of creativity, one emphasizing the novelty of systems, and its addition to an interactive application. We next introduce a generative e...

An extension to a non-linear offline method for generating features for image recognition is introduced. It aims at generating low-level features automatically when provided with some arbitrary image database. First, a general representation of prioritized pixel-neighbourhoods is described. Next, genetic programming is used to specify functions on...

We provide a short review of our recent work on the evolution of soft-bodied animats able to swim in a two-dimensional fluid-like environment. Our Artificial Life system, called \mbox{GReaNs}, is based on a model of a gene regulatory network (GRN), encoded in a linear genome, and a model of multicellular development. Animat bodies are created by co...

In this chapter, we will present three applications in which CGP can automatically generate novel image processing algorithms that compare to or exceed the best known conventional solutions. The applications fall into the areas of image preprocessing and classification.

This paper examines how models from ecology and evolutionary multi-agent systems can be used for creative applications. We outline a minimal, general specification for an ecosystem to be applied to the production of creative artefacts, based on spaces, materials, features and actions. Using this specification, we consider how basic evolutionary pri...

We present a theoretical model of animal morphogenesis construed as a self‐organized phenomenon emerging from a complex system made of a myriad of individual cell behaviors. It is implemented in an agent‐based simulation centered on the mechanic‐chemical coupling between cellular and genetic dynamics. The goal is to integrate the collective motion...

In this paper, we explore a generative art system de- signed to promote the creation of a diverse range of aesthetically pleasing images. We introduce our system, EvoEco, an agent- based pixel-level means of generating images based on artificial ecosystems. This art system is driven by interactive evolutionary computation, and further augmented usi...

In this paper, we introduce a new image database, consisting of examples of artists' work. Successful classification of this database suggests the capacity to automatically recognize an artist's aesthetic style. We utilize the notion of Transform-based Evolvable Features as a means of evolving features on the space, these features are then evaluate...

We explore a new definition of creativity — one which emphasizes the statistical capacity of a system to generate previously unseen patterns — and discuss motivations for this perspective in the context of machine learning. We show the definition to be computationally tractable, and apply it to the domain of generative art, utilizing a collection o...

In this paper, we use Genetic Programming (GP) to define a set of transforms on the space of greyscale images. The motivation is to allow an evolutionary algorithm means of transforming a set of image patterns into a more classifiable form. To this end, we introduce the notion of a transform-based evolvable feature (TEF), a moment value extracted f...

In biology, the importance of environmental feedback to the process of embryogenesis is well understood. In this paper we explore the introduction of a local fitness to an artificial developmental system, providing an artificial analogue to the natural phenomenon. First, we define a highly simplified model of vasculogenesis, an environment-based to...

We aim for a more rigorous discussion of "complexity" for Artificial Embryogeny. Initially, we review several existing measures from Biology and Mathematics. We argue that measures which rank complexity through a Turing machine, or measures of information contained in a genome about an environment, are not desireable here; Instead, we argue for mea...

We explore the use of the developmental environment as a spatial constraint on a model of Artificial Embryogeny, applied to the growth of structural forms. A Deva model is used to translate genotype to phenotype, allowing a Ge-netic Algorithm to evolve Plane Trusses. Genomes are ex-pressed in one of several developmental environments, and selected...

We present a model of artificial embryogeny, Deval, with discussion of design rationale. The motivation for an externally-evaluated test-bed for models in artificial embryogeny is discussed. We review a simple model of structural design, the plane truss. The Deval model is applied to the evolution of designs for trusses, showing that a variety of t...

We present a system for the automatic synthesis of classifiers. The CellNet system for generating binary pattern classifiers is used as a base for further experimentation. As in the original CellNet software, we evolve pattern recognisers (hunters). However, in this version called CellNet Co-Ev, we also evolve the patterns (prey) in a competitive c...

We describe the desire for a black box approach to pattern classification: a generic Autonomous Pattern Recognizer, which is capable of self-adapting to specific alphabets without human intervention. The CellNet software system is introduced, an evolutionary system that optimizes a set of pattern-recognizing agents relative to a provided set of fea...

A model for the co-evolution of patterns and classifiers is presented. The CellNet system for generating binary classifiers is used as a base for ex- perimentation. The CellNet system is extended to include a competitive co- evolutionary Genetic Algorithm, where patterns evolve as well as classifiers; This is facilitated by the addition of a set of...

The Bluenome Model of Development is introduced. The Bluenome model is a developmental model of Artificial Morphogenesis, inspired by biological development, instantiating a subset of two-dimensional Cellular Automata. The Bluenome model is cast as a general model, one which generates organizational topologies for finite sets of component types, as...

An evolutionary model of classifier synthesis is presented. The CellNet system for generating binary pattern classifiers is used as a base for experimentation [5]. CellNet is extended to include a competitive co-evolutionary mechanism, where patterns (prey) evolve as well as pattern classifiers (hunters). This is facilitated by the addition of a se...

The Bluenome Model of Development is introduced. The Bluenome model is a developmental model of Artificial Morphogenesis, inspired by biological development, instantiating a subset of two-dimensional Cellular Automata. The Bluenome model is cast as a general model, one which generates organizational topologies for finite sets of component types, as...