Leonardo
36.1 - World Spectators by Kaja Silverman. Stanford Univ. Press, Stanford, CA, 2000. 177 pp. ISBN: 0-8047-3831-9 (trade), 0-8047-3832-7 (paper)
LEON 36.1 - Part VII: Multimedia Part I
LEON 36.1 - A Methodology For Automating the Classification of Works of Art Using Neural Networks
LEON 36.1 - Thomas Wilfred and Intermedia: Seeking a Framework for Lumia
The most successful early-20th-century artist of colored light in the United States was undoubtedly Thomas Wilfred (1889–1968). In the 1920s, his “Lumia” compositions were praised by art critics and performed throughout the U.S. After initially embracing a musical analogy to explain Lumia, in the early 1930s he shifted to an analogy based on painting. In pursuit of this new context, Wilfred sought to legitimize Lumia through a relationship with the Museum of Modern Art in New York.
LEON 36.1 - On the Music of Emergent Behavior: What Can Evolutionary Computation Bring to the Musician?
In this article, the author focuses on issues concerning musical composition practices in which emergent behavior is used to generate musical material, musical form or both. The author gives special attention to the potential of cellular automata and adaptive imitation games for music-making. The article begins by presenting two case-study systems, followed by an assessment of their role in the composition of a number of pieces.
LEON 36.1 - Exploring Sound-Space with Interactive Genetic Algorithms
This paper describes a system that uses evolutionary computation to provide an interface to a complex sound-synthesis algorithm. The paper then considers a number of general issues to be considered when evolutionary computation is applied in artistic domains and the differences between interactive and non-interactive genetic algorithms.
LEON 36.1 - The NEXTPITCH Learning Classifier System: Representation, Information Theory and Performance
NEXTPITCH, a learning classifier system (LCS) using genetic algorithms, inductively learns to predict the next note in a musical melody. NEXTPITCH models human music learning by developing the rules that represent actual pitch transitions in the melody.
LEON 36.1 - GenJam in Perspective: A Tentative Taxonomy for GA Music and Art Systems
GenJam is an interactive genetic algorithm (GA) that models a human jazz improviser and performs regularly as the author's sideman on jazz gigs. GenJam learns to improvise full-chorus solos under the guidance of a human mentor and “trades fours” in real time with a human performer in “chase” choruses. In this article, the author first briefly describes GenJam's architecture, representations, genetic operators and performance characteristics. He then places GenJam in the context of a proposed taxonomy for GA-based music and art systems.
LEON 36.1 - The Aesthete in Pittsburgh: Public Sculpture in an Ordinary American City
There is a great deal of public art in Pittsburgh. Surveying some examples of this public sculpture suggests some general lessons about the role of such art. Art in public spaces needs to be accessible to the public. One way to make it so is to present local history, commemorating local sports heroes, politicians or artists. Public art also needs to be placed in a way that is sensitive to local history. Most public art in Pittsburgh is not successful because it does not deal with the interesting history of that city.