scholarly journals AffectGAN: Affect-Based Generative Art Driven by Semantics

2021 ◽  
Author(s):  
Theodoros Galanos ◽  
Antonios Liapis ◽  
Georgios N. Yannakakis
Keyword(s):  
Generative Art

Beyond Interactive Evolution: Expressing Intentions Through Fitness Functions

Leonardo ◽  
2016 ◽  
Vol 49 (3) ◽  
pp. 251-256 ◽  
Author(s):  
Penousal Machado ◽  
Tiago Martins ◽  
Hugo Amaro ◽  
Pedro H. Abreu
Keyword(s):  
Fitness Function ◽  
Interactive Art ◽  
Support Tool ◽  
Generative Art ◽  
Fitness Functions ◽  
Meta Level ◽  
Evolutionary Art ◽  
Creativity Support ◽  
The Creation ◽  
The Impact

Photogrowth is a creativity support tool for the creation of nonphotorealistic renderings of images. The authors discuss its evolution from a generative art application to an interactive evolutionary art tool and finally into a meta-level interactive art system in which users express their artistic intentions through the design of a fitness function. The authors explore the impact of these changes on the sense of authorship, highlighting the range of imagery that can be produced by the system.

scholarly journals Sztuka tworząca sztukę

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Paulina Tarara
Keyword(s):  
Generative Art

W pierwszej części artykułu przedstawię definicję oraz początki sztuki generatywnej (generative art) na przykładzie AARONa Harolda Cohena i Malującego Błazna Simona Coltona. W drugiej części opiszę współczesne dążenia w sztuce generatywnej na przykładzie maszyny imitującej Rembrandta oraz sieci przeciwstawnej Elgamalla.

scholarly journals Artificial intelligence in artistic practices

2021 ◽  
pp. 41-50
Author(s):  
Asmati Chibalashvili
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Visual Arts ◽  
Human Condition ◽  
Human Intervention ◽  
Basic Principles ◽  
Generative Art ◽  
Works Of Art ◽  
Artificial Intelligence Technology ◽  
Emotionally Intelligent

The article considers methods of involving artificial intelligence in artistic practices. Based on the analysis of ways to use this technology in visual arts and music, the basic principles of working with artificial intelligence technology are identified, including: imitation of historical art, implemented in projects The Next Rembrandt and Choral; generative art, which is found in the works “Hyperbolic Composition І” and “Hyperbolic Composition ІІ” of S. Eaton and also in the AIVA program (Artificial Intelligence Virtual Artist). The importance of the mechanisms of neurobiology in the process of working with artificial intelligence on the example of the project “Neural Zoo” of S. Crespo, Iamus program, in which the development of musical material is based on the principle of evolution, is stated. In the application Endel and in the opera “Emotionally intelligent” Artificially Intelligent Brainwave Opera» of E. Perlman, a neural network is used to read information about the human condition and its further processing for modification into a sound landscape or image. The development of artificial intelligence and its use in artistic practices opens up new opportunities, expanding both the field of authors of artistic content and attracting new audience. This phenomenon provokes many issues, including: the ability to think artificially of artificial intelligence, the ability to create works of art without human intervention, as well as issues related to copyright.

From Swarm Art Toward Ecosystem Art

2012 ◽  
Vol 3 (3) ◽  
pp. 1-18 ◽  
Author(s):  
Stefan Bornhofen ◽  
Vincent Gardeux ◽  
Andréa Machizaud
Keyword(s):  
Visual Information ◽  
Simulation Optimization ◽  
Search Space ◽  
Ecosystem Dynamics ◽  
Natural Ecosystems ◽  
Decentralized System ◽  
Generative Art ◽  
Artistic Creation ◽  
Creation Process ◽  
Intelligent Behavior

Swarm intelligence deals with the study of collectively intelligent behavior that emerges from a decentralized system of non-intelligent individual agents. The concept is widely used in the fields of simulation, optimization or robotics, but less known in the domain of generative art. This paper presents the swarm paradigm in the context of artistic creation, and more particularly explores the interest of enhancing swarm models with dynamics inspired from natural ecosystems. The authors introduce an energy budget to the agents of a swarm system, and show how mapping the energy level to visual information such as line width or color, combined with mechanisms such as resource chasing and consumption, enriches the search space of possible images. Moreover, the authors highlight that the approach allows the user to partially control the creation process of the drawings. The authors argue that the exploration of ecosystem dynamics in generative systems may open up novel artistic opportunities and shift the perspective from swarm art toward ecosystem art.

scholarly journals Avoiding the Inherent Limitations in Datasets Used for Measuring Aesthetics When Using a Machine Learning Approach

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Adrian Carballal ◽  
Carlos Fernandez-Lozano ◽  
Nereida Rodriguez-Fernandez ◽  
Luz Castro ◽  
Antonino Santos
Keyword(s):  
State Of The Art ◽  
Learning Approach ◽  
Aesthetic Value ◽  
Experimental Conditions ◽  
Generative Art ◽  
Machine Learning Approach ◽  
Evolutionary Art ◽  
The Aesthetic ◽  
Psychological Experiments

An important topic in evolutionary art is the development of systems that can mimic the aesthetics decisions made by human begins, e.g., fitness evaluations made by humans using interactive evolution in generative art. This paper focuses on the analysis of several datasets used for aesthetic prediction based on ratings from photography websites and psychological experiments. Since these datasets present problems, we proposed a new dataset that is a subset of DPChallenge.com. Subsequently, three different evaluation methods were considered, one derived from the ratings available at DPChallenge.com and two obtained under experimental conditions related to the aesthetics and quality of images. We observed different criteria in the DPChallenge.com ratings, which had more to do with the photographic quality than with the aesthetic value. Finally, we explored learning systems other than state-of-the-art ones, in order to predict these three values. The obtained results were similar to those using state-of-the-art procedures.

New Naturality: A Generative Approach to Art and Design

Leonardo ◽  
2002 ◽  
Vol 35 (3) ◽  
pp. 291-294 ◽  
Author(s):  
Celestino Soddu
Keyword(s):  
Virtual Environments ◽  
Artificial Life ◽  
3D Model ◽  
Generative Art ◽  
Art And Design ◽  
The Real ◽  
Design Concepts ◽  
Design Idea ◽  
Generative Approach

In the field of generative art and design, design concepts are represented as code. This generative code functions as DNA does in nature. It uses artificial life to generate a multiplicity of possible artworks, artificial events, architectures and virtual environments. In the generative approach the real artwork is not merely a product, such as an image or 3D model. The generative artwork is an Idea-Product. It represents an artificial species able to generate an endless sequence of individual events, each one different, unique and unrepeatable but belonging to the same identifiable design Idea. The author's project, Argenia, realizes the “new naturality” of artificial objects.

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