Generative Systems Art

In this unique book the author explores the history of pioneering computer art and its contribution to art history by way of examining Ernest Edmonds’ art from the late 1960s to the present day. Edmonds’ inventions of new concepts, tools and forms of art, along with his close involvement with the communities of computer artists, constructive artists and computer technologists, provides the context for discussion of the origins and implications of the relationship between art and technology. Drawing on interviews with Edmonds and primary research in archives of his work, the book offers a new contribution to the history of the development of digital art and places Edmonds’ work in the context of contemporary art history.

Summary Generative Art presents both the technique and the beauty of algorithmic art. The book includes high-quality examples of generative art, along with the specific programmatic steps author and artist Matt Pearson followed to create each unique piece using the Processing programming language. About the Technology Artists have always explored new media, and computer-based artists are no exception. Generative art, a technique where the artist creates print or onscreen images by using computer algorithms, finds the artistic intersection of programming, computer graphics, and individual expression. The book includes a tutorial on Processing, an open source programming language and environment for people who want to create images, animations, and interactions. About the Book Generative Art presents both the techniques and the beauty of algorithmic art. In it, you'll find dozens of high-quality examples of generative art, along with the specific steps the author followed to create each unique piece using the Processing programming language. The book includes concise tutorials for each of the technical components required to create the book's images, and it offers countless suggestions for how you can combine and reuse the various techniques to create your own works. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book. What's Inside The principles of algorithmic art A Processing language tutorial Using organic, pseudo-random, emergent, and fractal processes ========================================​========= Table of Contents Part 1 Creative Coding Generative Art: In Theory and Practice Processing: A Programming Language for ArtistsPart 2 Randomness and Noise The Wrong Way to Draw A Line The Wrong Way to Draw a Circle Adding Dimensions Part 3 Complexity Emergence Autonomy Fractals

Eighteen Generative Systems artists share their experimental electronic images, made at the dawn of the electronic era

Reflecting the dynamic creativity of its subject, this definitive guide spans the evolution, aesthetics, and practice of today’s digital art, combining fresh, emerging perspectives with the nuanced insights of leading theorists. Showcases the critical and theoretical approaches in this fast-moving discipline Explores the history and evolution of digital art; its aesthetics and politics; as well as its often turbulent relationships with established institutions Provides a platform for the most influential voices shaping the current discourse surrounding digital art, combining fresh, emerging perspectives with the nuanced insights of leading theorists Tackles digital art’s primary practical challenges – how to present, document, and preserve pieces that could be erased forever by rapidly accelerating technological obsolescence Up-to-date, forward-looking, and critically reflective, this authoritative new collection is informed throughout by a deep appreciation of the technical intricacies of digital art

Generative Art: Algorithms as Artistic Tool presents both simple programming concepts and generative art principles in the same book. Generative Art, a relatively new form of art, is the art of the algorithm where an artist must carefully design the nature of the work and then implement it as a computer program. This book presents a set of novel approaches to this subject. Existing books on this subject confront the topic through the lens of programming. This book does that, but also presents approaches to creating art using art and design best practices. Content is arranged according to the problem that is to be solved. Readers will have access to code used in the book through the book's web site and video tutorials are also available for each chapter.

An examination of machine learning art and its practice in new media art and music. Over the past decade, an artistic movement has emerged that draws on machine learning as both inspiration and medium. In this book, transdisciplinary artist-researcher Sofian Audry examines artistic practices at the intersection of machine learning and new media art, providing conceptual tools and historical perspectives for new media artists, musicians, composers, writers, curators, and theorists. Audry looks at works from a broad range of practices, including new media installation, robotic art, visual art, electronic music and sound, and electronic literature, connecting machine learning art to such earlier artistic practices as cybernetics art, artificial life art, and evolutionary art. Machine learning underlies computational systems that are biologically inspired, statistically driven, agent-based networked entities that program themselves. Audry explains the fundamental design of machine learning algorithmic structures in terms accessible to the nonspecialist while framing these technologies within larger historical and conceptual spaces. Audry debunks myths about machine learning art, including the ideas that machine learning can create art without artists and that machine learning will soon bring about superhuman intelligence and creativity. Audry considers learning procedures, describing how artists hijack the training process by playing with evaluative functions; discusses trainable machines and models, explaining how different types of machine learning systems enable different kinds of artistic practices; and reviews the role of data in machine learning art, showing how artists use data as a raw material to steer learning systems and arguing that machine learning allows for novel forms of algorithmic remixes.

Scribing - the practice of visually mapping a group's content in real time, as people talk - is increasingly used across sectors and around the globe to bring human ideas and interaction alive through words and images, thus activating the social field in a unique and participatory way.Scribing is an evolving art form whose potential is only just beginning to be fully realized. This book will provide a much needed framework for scribing and, on a larger level, for seeing possibilities of connecting inner and outer lives, art and the social realm.

This comprehensive book gives an up-to-date survey of the relevant bioinspired computing research fields – such as evolutionary computation, artificial life, swarm intelligence and ant colony algorithms – and examines applications in art, music and design. The editors and contributors are researchers and artists with deep experience of the related science, tools and applications, and the book includes overviews of historical developments and future perspectives.