Computational Intelligence in Music, Sound, Art and Design
Springer International Publishing (Verlag)
978-3-319-55749-6 (ISBN)
The 24 revised full papers presented were carefully reviewed and selected from 29 submissions. The papers cover a wide range of topics and application areas, including: generative approaches to music, graphics, game content, and narrative; music information retrieval; computational aesthetics; the mechanics of interactive evolutionary computation; computer-aided design; and the art theory of evolutionary computation.
Algorithmic Songwriting with ALYSIA.- On Symmetry, Aesthetics and Quantifying Symmetrical Complexity.- Towards Polyphony Reconstruction Using Multidimensional Multiple Sequence Alignment.- Melody Retrieval and Classification Using Biologically-Inspired Techniques.- Evolved Aesthetic Analogies to Improve Artistic Experience.- Deep Artificial Composer: A Creative Neural Network Model for Automated Melody Generation.- A Kind of Bio-inspired Learning of mUsic stylE.- Using Autonomous Agents to Improvise Music Compositions in Real-time.- Generating Polyphonic Music Using Tied Parallel Networks.- Mixed-initiative Creative Drawing with webIconoscope.- Clustering Agents for the Evolution of Autonomous Musical Fitness.- EvoFashion: Customising Fashion Through Evolution.- A Swarm Environment for Experimental Performance and Improvisation.- Niche Constructing Drawing Robots.- Automated Shape Design by Grammatical Evolution.- Evolutionary Image Transition Using Random Walks.- Evaluation Rules forEvolutionary Generation of Drum Patterns in Jazz Solos.- Assessing Augmented Creativity: Putting a Lovelace Machine for Interactive Title Generation through a Human Creativity Test.- Play It again: Evolved Audio Effects and Synthesizer Programming.- Fashion Design Aid System with Application of Interactive Genetic Algorithms.- Generalization Performance of Western Instrument Recognition Models in Polyphonic Mixtures with Ethnic Samples.- Exploring the Exactitudes Portrait Series with Restricted Boltzmann Machines.- Evolving Mondrian-Style Artworks.- Predicting Expressive Bow Controls for Violin and Viola.
| Erscheinungsdatum | 08.04.2017 |
|---|---|
| Reihe/Serie | Lecture Notes in Computer Science | Theoretical Computer Science and General Issues |
| Zusatzinfo | X, 371 p. 169 illus. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 587 g |
| Themenwelt | Informatik ► Theorie / Studium ► Algorithmen |
| Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik | |
| Schlagworte | Agents • Algorithm analysis and problem complexity • algorithms • algorithms and data structures • ant colony optimization • Applications • Artificial Intelligence • artificial intelligence (incl. robotics) • Bioinformatics • classification • Computer applications in the arts and humanities • Computer Appl. in Arts and Humanities • Computer Science • computer vision • conference proceedings • Data Mining • data mining and knowledge discovery • Distributed Systems • evolutionary algorithm • Expert systems / knowledge-based systems • Genetic algorithms • genetic programming • Heuristics • Image Analysis • Image Processing • image processing and computer vision • Informatics • Information Retrieval • machine learning • Mathematical and statistical software • Maths for computer scientists • Multi-agent Systems • Neural networks • Probability and Statistics in Computer Science • Research • Robotics • sequence alignment • Software engineering • Swarm intelligence • theoretical computer science |
| ISBN-10 | 3-319-55749-1 / 3319557491 |
| ISBN-13 | 978-3-319-55749-6 / 9783319557496 |
| Zustand | Neuware |
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