Emergent Patterns in Dance Improvisation And Choreography

A choreographer can only overlook a certain amount of complexity, which is why the spatial organization of most choreographed ballets is more or less the same. With more time it is possible to create more intricate patterns but even then spatial variability is limited by the fact that relations between dancers have to be communicated to the dancers.

Complexity theory has shown that a central governing agent is not necessary for the emergence of intricate patterns or cooperative behavior. However, simply transferring the rules that govern for instance the flocking of birds to dance doesn't work. These rules only apply under certain conditions. One would therefore have to develop rules specific to dance. It should be emphasized that ANY choreography is governed by a set of IMPLICIT rules. By making those rules EXPLICIT their hidden potential in the form of alternative forms of organization can be revealed.

Summary

• Definition: a complex system is one in which many different components interact, whereby the properties of the individual components do not fully explain the properties of the system as a whole.

• Characteristic of complex systems: the coupling between component parts and system, or between individual and group.

• Alternative definition: the (algorithmic) complexity of an object is defined as the length of the shortest program (or description) which generates the object.

• Example: 0000000000 and 0101010101. The first sequence can be succintly described as a sequence of ten zeroes while the second can be described as five alternating 0’s and 1’s. Now take a look at the following sequence: 0010111101100. The shortest possible description of this sequence is the sequence itself. This last sequence can therefore be called the most complex.

• Applied to movements: constantly moving every conceivable part of the body may at first look complex, but is in fact quite simple: the task move every part of the body will produce a series of sequences that all look more or less the same.

• Complexity matters: The appraisal structure of interest depends on novelty, complexity and coping potential

• The more complex a system becomes, the more information is needed to describe it, in terms of a choreography: the more instructions one has to give to the dancers. With more time it is certainly possible to create more complex works, but even then there are limits as to what can be tried out. Although history provides a starting point each individual will first have to arrive at the complexity of previous works before being able to transcend it.

• Emergent Choreography: The literature on complex systems offers a different paradigm for bringing about complexity.

• The collective motion of birds, fish and bacteria, the movements of large crowds of people, traffic jams, etc. can be modelled using models consisting of a number of individual agents with some simple rules guiding their individual behavior and their interactions with other agents.

• Instead of applying complexity theory to dance, one would have to design a complexity theory of dance. Models of crowding or flocking reduce multi organ organisms to dots on a screen. Under some conditions this modelling approach may apply to groups of humans, but in dance dancers will instantly be at a loss as to what to do. The rules are underspecified (HOW to walk, move etc.).

• My own approach has been to extract rules from the interaction of dancers and to then re-apply those rules to the dance and to see where a conflict or a ‘decision void’ arises.

Publications

Hagendoorn, I.G. (2002), ‘Emergent patterns in dance improvisation and choreography’, Proceedings of the International Conference on Complex Systems.

Hagendoorn, I.G. (2004), ‘De wereld als wiskundig netwerk’. De Academische Boekengids (in Dutch).

References

N. Johnson (2007), Two's Company, Three's Complexity (Chapter 1).

M. Gell-Mann (1995), What Is Complexity? Complexity, Vol. 1, no. 1.

M. Gell-Mann (2002), Plectics: The study of simplicity and complexity. Europhysics News Vol. 33 No. 1 (Highly recommended).

A.-L. Barabási and E. Bonabeau (2003), Scale-free networks. Scientific American 288, 60-69.

S. H. Strogatz (2001), Exploring complex networks. Nature 410: 268-276.

Z. Neda, E. Ravasz, Y. Brechet, T. Vicsek and A.-L. Barabási (2000), Self-organizing processes: The sound of many hands clapping. Nature 403, 849-850.

Steven Strogatz: Sync. The Emerging Science of Spontaneous Order, 2003.

Murray Gell-Mann: The Quark and the Jaguar, 1994.

Neil Johnson: Two's Company, Three's Complexity, 2007.

John Holland: Hidden Order, 1996.

Albert-Laszlo Barabasi: Linked. The New Science of Networks, 2002.

Dirk Helbing [Ed.]: Managing Complexity: Insights, Concepts, Applications, 2008.

Links

Communications from the Lab. The labyrinth scene is based on a limited set of movements and some simple rules.

An excerpt from Koyaanisqatsi.