Olivier Michel – författare

Nowadays, developers have to face the proliferation of hardware and software environments, the increasing demands of the users, the growing number of p- grams and the sharing of information, competences and services thanks to the generalization ofdatabasesandcommunication networks. Aprogramisnomore a monolithic entity conceived, produced and ?nalized before being used. A p- gram is now seen as an open and adaptive frame, which, for example, can - namically incorporate services not foreseen by the initial designer. These new needs call for new control structures and program interactions. Unconventionalapproachestoprogramminghavelongbeendevelopedinv- iousnichesandconstituteareservoirofalternativewaystofacetheprogramming languages crisis. New models of programming (e. g. , bio-inspired computing, - ti?cialchemistry,amorphouscomputing,. . . )arealsocurrentlyexperiencinga renewed period of growth as they face speci?c needs and new application - mains. These approaches provide new abstractions and notations or develop new ways of interacting with programs. They are implemented by embedding new sophisticated data structures in a classical programming model (API), by extending an existing language with new constructs (to handle concurrency, - ceptions, open environments, . . . ), by conceiving new software life cycles and program executions (aspect weaving, run-time compilation) or by relying on an entire new paradigm to specify a computation. They are inspired by theoretical considerations (e. g. , topological, algebraic or logical foundations), driven by the domain at hand (domain-speci?c languages like PostScript, musical notation, animation, signal processing, etc. ) or by metaphors taken from various areas (quantum computing, computing with molecules, informationprocessing in - ological tissues, problem solving from nature, ethological and social modeling).

Nowadays, developers have to face the proliferation of hardware and software environments, the increasing demands of the users, the growing number of p- grams and the sharing of information, competences and services thanks to the generalization ofdatabasesandcommunication networks. Aprogramisnomore a monolithic entity conceived, produced and ?nalized before being used. A p- gram is now seen as an open and adaptive frame, which, for example, can - namically incorporate services not foreseen by the initial designer. These new needs call for new control structures and program interactions. Unconventionalapproachestoprogramminghavelongbeendevelopedinv- iousnichesandconstituteareservoirofalternativewaystofacetheprogramming languages crisis. New models of programming (e. g. , bio-inspired computing, - ti?cialchemistry,amorphouscomputing,. . . )arealsocurrentlyexperiencinga renewed period of growth as they face speci?c needs and new application - mains. These approaches provide new abstractions and notations or develop new ways of interacting with programs. They are implemented by embedding new sophisticated data structures in a classical programming model (API), by extending an existing language with new constructs (to handle concurrency, - ceptions, open environments, . . . ), by conceiving new software life cycles and program executions (aspect weaving, run-time compilation) or by relying on an entire new paradigm to specify a computation. They are inspired by theoretical considerations (e. g. , topological, algebraic or logical foundations), driven by the domain at hand (domain-speci?c languages like PostScript, musical notation, animation, signal processing, etc. ) or by metaphors taken from various areas (quantum computing, computing with molecules, informationprocessing in - ological tissues, problem solving from nature, ethological and social modeling).

Generally, spontaneous pattern formation phenomena 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 self-organized and architectural. 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 placed 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.  Altogether, the aim of this work is to provide a framework for and examples of a larger class of “self-architecturing” systems, while addressing fundamental questions such as > How do biological organisms carry out morphogenetic tasks so reliably? > Can we extrapolate their self-formation capabilities to engineered systems?> Can physical systems be endowed with information (or informational systems be embedded in physics) so as to create autonomous morphologies and functions?> What are the core principles and best practices for the design and engineering of such morphogenetic systems? The intended audience consists of researchers and graduate students who are working on, starting to work on, or interested in programmable self-organizing systems in a wide range of scientific fields, including computer science, robotics, bioengineering, control engineering, physics, theoretical biology, mathematics, and many others.