Towards A Generic Computational Intelligence Library: Preventing Insanity

This paper proposes a library for computational intelligence using functional programming to address the complexities in algorithm implementation and highlighting specific concerns that are often ignored in the algorithm descriptions. Useful abstractions, common in the paradigm of functional programming, are used to make implementation specifics of algorithms part of the algorithm definition, resulting in the tracking of these effects, together with the control of the effects. Effects, requiring management within an algorithm, include the use of pseudo-random number generators, writing data to files or the console, or providing the control parameter configuration of the algorithm in an experiment. By defining the units of work for an algorithm in a general and generic form, composition of these different algorithmic units is possible, thereby creating larger, more complex computational units. The software library providing such reusable, peer-reviewed compos able computational unit, is called CIlib.