Over a century ago, William James proposed that people search through memory much as they rummage through a house looking for lost keys. We scour our environments for territory, food, mates, and information. We search for items in visual scenes, for historical facts, and for the best deals on Internet sites; we search for new friends to add to our social networks, and for solutions to novel problems. What we find is always governed by how we search and by the structure of the environment.
This volume presents the most up-to-date collection of neural network models of music and creativity gathered together in one place. Chapters by leaders in the field cover new connectionist models of pitch perception, tonality, musical streaming, sequential and hierarchical melodic structure, composition, harmonization, rhythmic analysis, sound generation, and creative evolution. The collection combines journal papers on connectionist modeling, cognitive science, and music perception with new papers solicited for this volume. It also contains an extensive bibliography of related work.
As one of our highest expressions of thought and creativity, music has always been a difficult realm to capture, model, and understand. The connectionist paradigm, now beginning to provide insights into many realms of human behavior, offers a new and unified viewpoint from which to investigate the subtleties of musical experience.