History
Although Artificial Intelligence and Discrete Optimization had known and reasoned about Constraint Satisfaction Problems for many years, it was not until the early 1990s that this process for solving large CSPs had been codified in algorithmic form. Early on, Mark Johnston of the Space Telescope Science Institute looked for a method to schedule astronomical observations on the Hubble Space Telescope. In the process, he created a neural network capable of solving a toy N-queens problem (for 1024 queens). Steven Minton and Andy Philips analyzed the neural network algorithm and separated it into two phases: (1) an initial assignment using a greedy algorithm and (2) a conflict minimization phases (later to be called "min-conflicts"). A paper was written and presented at AAAI-90; Philip Laird provided the mathematical analysis of the algorithm.
Subsequently, Mark Johnston and the STScI staff used min-conflicts to schedule astronomers' experiment time on the Hubble Space Telescope.
Read more about this topic: Min-conflicts Algorithm
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