Annealing Strategies

This system optimises and searches a chaotic parameter space using the process of simulated annealing. This algorithm mimics the physical mechanism of gradually cooling metal in order to remove internal stresses and strengthen it. This process is similar to a hill climbing algorithm, with the addition of a 'temperature' coefficient that allows for local minima and maxima to be escaped from. Random decisions are allowed with respect to this coefficient, meaning the system is volatile and explorative at high temperatures and more conservative at low temperatures. As the system is cooled the system hones in on an optimised solution. 

A single input value is used which is mapped onto a three-dimensional parameter space.  The sound generating guts of the system are a digital emulation of Peter Blasser's (Ciat-Lonbarde) fourses algorithm. This engine takes 24 parameters, which are reduced in dimensionality to a single input. The output of the system is measured in decibels according to a perceptual loudness descriptor. The sim-annealing algorithm attempts to find at which input parameter the quietest output is produced. The system's agency is its exploratory journey to an optimised solution.

Link to audio here

 

 

 

 

 A rough emulation of the simualted annealing process. One dimensional input is mapped to 24 dimensional parameter space. dB output is measured. The system hones in on the value of -74dB.

A rough emulation of the simualted annealing process. One dimensional input is mapped to 24 dimensional parameter space. dB output is measured. The system hones in on the value of -74dB.