Jake, I presume you're talking about GP.  GPNodes, GPTrees, and  

GPIndividuals all basically work like this: after a population is  

evaluated, typically the individuals undergo breeding to create new  

individuals, and then are usually eliminated.  Breeding works by  

cloning subtrees, and ultimately nodes, from the old individuals to  

form new individuals.  The clone method used is lightClone(), which  

ultimately calls clone() underneath.



So let's say you've made got a GPNode called 'foo' which has an  

ArrayList called foo.bar.  'foo' is located in some GPIndividual, and  

the GP system has decided to copy that individual, and the subtree  

where 'foo' is located, to create a new child for the next  

generation.  We call foo.clone().  This creates a new object (call it  

foo2).  foo2.bar is pointing to the same ArrayList as foo.bar now.   

Now we create another new child from foo (foo's lucky!) called foo3.   

foo3.bar and foo2.bar BOTH are pointing to the same ArrayList as  

foo.bar is.



This may be what you want, but I'm guessing it's not.  Because now you  

evaluate the new child individual that holds foo2.  It adds something  

to the foo2.bar ArrayList.  When you get around to evaluating the  

individual that has foo3, it ALSO will have that thing added into its  

ArrayList because it's the same ArrayList.  You probably were hoping  

them to have separate ArrayLists is my guess.



To do that, you override the GPNode clone method for your particular  

GPNode subclass to call super.clone(), and then say something like:



	bar = (ArrayList)(bar.clone());



Now foo2 and foo3 have their own copies of the ArrayList, different  

from the original one in foo, each storing what foo.bar had inside it,  

but able to add their own independent stuff without stepping on each  

others' toes.



Sean



On Jan 22, 2010, at 5:13 PM, Jake Pacheco wrote:



> Specifically, I have a node that is meant to calculate the zero lag

> exponential moving average of its child's value. This requires the  

> node

> having access to its own value on the previous evaluation, as well  

> as the

> child's value for several evaluations back. The way I implemented  

> this, the

> node stores its value in a variable after calculation, and adds the  

> child's

> value to an ArrayList. However, I am not sure if these are preserved  

> through

> to the next evaluation, or, if they are preserved through evaluations,

> whether they will be empty once the next generation starts.