使用欧洲法院21进行遗传编程,我正在寻找关于如何序列化ec.Individual的建议(在成功之后(?)进化)。
诀窍是,我需要在稍后阶段反序列化这个GP,并在ECJ框架之外执行it...preferably (在ECJ框架中工作时,似乎有很多脚手架涉及到“执行”GP,因为这实际上是为了改进事物,而不是“运行”它)。
我几乎有这样的东西:
public static void main (String [] args) {
File f = new File("./my.params");
if (!f.exists() ) {
throw new InvalidParameterException(f.getName() + " does NOT exist");
}
ParameterDatabase pd = new ParameterDatabase(f, new String []{f.getCanonicalPath()});
Output output = ec.Evolve.buildOutput();
EvolutionState evs = ec.Evolve.initialize(pd, 0,output);
evs.run(EvolutionState.C_STARTED_FRESH);
Individual [] individuals = ((SimpleStatistics)evs.statistics).getBestSoFar();
String bestIndividStr = "";
for (Individual individual : individuals) {
bestIndividStr = printToLog(evs, individual);
}
Species s = individuals[0].species;
s = new GPSpecies();
Individual gpInd = s.newIndividual(evs, new LineNumberReader(new StringReader(bestIndividStr)));
}
private static String printToLog(EvolutionState evs, Individual individual) {
String bestIndividStr;
ByteArrayOutputStream baos = new ByteArrayOutputStream();
PrintWriter pw = new PrintWriter(baos);
individual.printIndividual(evs, pw);
pw.append(System.lineSeparator());
pw.close();
bestIndividStr = baos.toString();
LoggerFactory.getLogger(Evolve.class).info("Best Dude: \n{}",bestIndividStr);
return bestIndividStr;
}好的,这里的一些问题是:
gpInd为printIndividual(..)生成的文本输出编写自己的解析器和计算堆栈不应该那么困难,但如果有一种更简单(内置)的方法,我宁愿不这样做。
PS:到目前为止,我所做的是基于本教程构建的
发布于 2015-04-16 19:42:57
我也有过类似的问题。我的解决方案是通过子类GPNode创建个人的XML表示。下面的源代码显示了适当的实现。
public abstract class XMLGPNode extends GPNode {
/**
*
*/
private static final long serialVersionUID = 2732707537997825895L;
public StringBuilder makeXMLTree() {
DocumentBuilderFactory docFactory = DocumentBuilderFactory.newInstance();
DocumentBuilder docBuilder = null;
StringBuilder sb = new StringBuilder();
try {
docBuilder = docFactory.newDocumentBuilder();
Document doc = docBuilder.newDocument();
makeXMLTree(doc, null);
TransformerFactory transformerFactory = TransformerFactory.newInstance();
Transformer transformer;
transformer = transformerFactory.newTransformer();
DOMSource source = new DOMSource(doc);
StringWriter sw = new StringWriter();
StreamResult result = new StreamResult(sw);
// Output to console for testing
// StreamResult result = new StreamResult(System.out);
transformer.transform(source, result);
sb.append(new String(sw.getBuffer()));
} catch (TransformerConfigurationException e) {
// TODO Auto-generated catch block
e.printStackTrace();
} catch (ParserConfigurationException e) {
// TODO Auto-generated catch block
e.printStackTrace();
} catch (TransformerException e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
return sb;
}
private void makeXMLTree(Document doc, Element parent) {
Element child = doc.createElement(toString());
if (parent==null) {
doc.appendChild(child);
} else {
parent.appendChild(child);
}
if (children.length > 0) {
for(int x=0; x<children.length; x++) {
((XMLGPNode)children[x]).makeXMLTree(doc, child);
}
}
}然后,可以在问题中序列化最终个体,以便将其保存或传输到另一个应用程序,或加载它以进行新的评估。
下面的代码片段显示了makeXMLTree-method调用GPProblem实现的evaluate-method中的根节点。
public void evaluate(final EvolutionState state,
final Individual ind,
final int subpopulation,
final int threadnum) {
if (!ind.evaluated) { // don't bother reevaluating
int hits = 0;
...
...
transformationType = new TransformationType(TransformationType.TYPE.values()[state.random[threadnum].nextInt(TransformationType.MAX_INPUT_TYPES)]);
((GPIndividual)ind).trees[0].child.eval(state,threadnum,input,stack,((GPIndividual)ind),this);
XMLGPNode child = (XMLGPNode)((GPIndividual)ind).trees[0].child;
**String individual = child.makeXMLTree().toString();**... ...
https://stackoverflow.com/questions/24373981
复制相似问题