Galapagos is a small Genetic Programming experiment written in Clojure.
Koza's original Genetic Programming implementation is written in Common Lisp. I had not forseen any difficulties with implementing a Genetic Programming system in Clojure since it is also a Lisp. However there is one major difference between Clojure and Common Lisp that makes writing a Genetic Programing system in Clojure more difficult.
In Clojure a list is immutable. In Common Lisp is is possible to destructively modify a list by replacing an element in the list. This can be done for example using the Common Lisp setf macro.
It obviously possible to write functions that create a new copy of a program where a certain branch is replaced or where two branches from different parents have been crossed over. However these functions do not feel very clean. Instead it is probably better to come up with a different representation for the program using a data structure that is mutable in Clojure.
Vectors are a good choice. However maps might also be a good choice. With maps we can add lots of extra information to the program tree like the index of each node and the depth of each node. These pieces of information are very useful when you are performing the core Genetic Programming operations.
I am going to have to think on this a bit before I continue.
The thing about Genetic Programming is that you want the program trees to be mutable. In Clojure the list datastructure is not mutable. Instead we will have to use a different datastructure. The obvious choices are vector and map.
Map is probably a better choice because then we could associate additional information with each node. For example the index of the node and the depth of the node are useful pieces of information when performing crossover and mutations.
One remaining question then is if we should have :left-child and :right-child keys in the map that are associated with the left and right child nodes or if we should have a :children key that is associated a vector of child nodes. This way we could have an arbitrary number of child nodes. I think I will go with an arbitrary number of children since this will be very useful in the case of polynomials.
It is probably a good idea to have a root node for the program tree. Compare this with how Knuth does linked lists in the Art of Computer programming.
The root node has one child. This child is the actual root of the tree. The purpose of the root node is for the algorithms to be able to treat the actual root node of the tree the same as all the other nodes.
Add a struct called node that contains the following keys.
:function :children :depth :index
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