Description
The goal of this thesis is to explore and present a range of approaches to “algorithmic choreography.” In the context of this thesis, algorithmic choreography is defined as choreography with computational influence or elements. Traditionally, algorithmic choreography, despite containing works

The goal of this thesis is to explore and present a range of approaches to “algorithmic choreography.” In the context of this thesis, algorithmic choreography is defined as choreography with computational influence or elements. Traditionally, algorithmic choreography, despite containing works that use computation in a variety of ways, has been used as an umbrella term for all works that involve computation.
This thesis intends to show that the diversity of algorithmic choreography can be reduced into more specific categories. As algorithmic choreography is fundamentally intertwined with the concept of computation, it is natural to propose that algorithmic choreography works be separated based on a spectrum that is defined by the extent of the involvement of computation within each piece.
This thesis seeks to specifically outline three primary categories that algorithmic works can fall into: pieces that involve minimal computational influence, entirely computationally generated pieces, and pieces that lie in between. Three original works were created to reflect each of these categories. These works provide examples of the various methods by which computation can influence and enhance choreography.
The first piece, entitled Rαinwater, displays a minimal amount of computational influence. The use of space in the piece was limited to random, computationally generated paths. The dancers extracted a narrative element from the random paths. This iteration resulted in a piece that explores the dancers’ emotional interaction within the context of a rainy environment. The second piece, entitled Mymec, utilizes an intermediary amount of computation. The piece sees a dancer interact with a projected display of an Ant Colony Optimization (ACO) algorithm. The dancer is to take direct inspiration from the movement of the virtual ants and embody the visualization of the algorithm. The final piece, entitled nSkeleton, exhibited maximal computational influence. Kinect position data was manipulated using iterative methods from computational mathematics to create computer-generated movement to be performed by a dancer on-stage.
Each original piece was originally intended to be presented to the public as part of an evening-length show. However, due to the rise of the COVID-19 pandemic caused by the novel coronavirus, all public campus events have been canceled and the government has recommended that gatherings with more than 10 people be entirely avoided. Thus, the pieces will instead be presented in the form of a video published online. This video will encompass information about the creation of each piece as well as clips of choreography.

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Details

Title
  • Exploring the Range of Algorithmic Choreography
Contributors
Agent
Date Created
2020-05

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