public Expression CrossOver(Expression t1, Expression t2, double probswap = 0.7, bool top = true)
{
if (RndGenerator.RndDouble() < probswap && !top)
{
return(t2);
}
var result = t1;
var childrenExpsT1 = GetChildren(t1);
var childrenExpsT2 = GetChildren(t2);
if (childrenExpsT1 == null || childrenExpsT2 == null)
{
return(result);
}
var newChildren = new List <Expression>();
foreach (var expression in childrenExpsT1)
{
newChildren.Add(CrossOver(expression, childrenExpsT2[RndGenerator.RndInt32(0, childrenExpsT2.Count)], probswap, false));
}
return(UpdateChildren(result, newChildren));
}
public static Expression MakeRandomTree(ParameterExpression[] paramExps, int maxTreeDepth = 4,
double fpr = 0.5, double ppr = 0.6)
{
if (RndGenerator.RndDouble() < fpr && maxTreeDepth > 0)
{
(var funcExp, var pc) = ExpFactory.Choice();
var children = new Expression[pc];
for (int i = 0; i < pc; i++)
{
children[i] = MakeRandomTree(paramExps, maxTreeDepth - 1, fpr, ppr);
}
return(funcExp(children));
}
else if (RndGenerator.RndDouble() < ppr)
{
return(paramExps[RndGenerator.RndInt32(0, paramExps.Length)]);
}
else
{
return(Expression.Constant(RndGenerator.RndInt32(0, 10)));
}
}
public Func <int, int, int> Evolve(ParameterExpression[] pc, int popsize,
Func <List <ValueTuple <Func <int, int, int>, Expression> >, List <ValueTuple <long, Func <int, int, int>, Expression> > > rankfunction, int maxgen = 500, double mutationrate = 0.1,
double breedingreate = 0.4, double pexp = 0.7, double pnew = 0.05)
{
//返回一个随机数，通常是一个较小的数
//pexp的取值越小，我们得到的随机数就越小
Func <int> selectIndex = () => (int)(Math.Log(RndGenerator.RndDouble()) / Math.Log(pexp));
// 创建一个随机的初始种群
var population = new List <ValueTuple <Func <int, int, int>, Expression> >(popsize);
for (int i = 0; i < popsize; i++)
{
var exp = MakeRandomTree(pc);
var func = exp.Compile <Func <int, int, int> >(pc);
population.Add((func, exp));
}
List <ValueTuple <long, Func <int, int, int>, Expression> > scores = null;
for (int i = 0; i < maxgen; i++)
{
scores = rankfunction(population);
_outputWriter?.Invoke(scores[0].Item1);
if (scores[0].Item1 == 0)
{
break;
}
// 取两个最优的程序
var newpop = new List <ValueTuple <Func <int, int, int>, Expression> >()
{
(scores[0].Item2, scores[0].Item3),
(scores[1].Item2, scores[1].Item3)
};
//构造下一代
while (newpop.Count < popsize)
{
if (RndGenerator.RndDouble() > pnew)
{
var exp = Mutate(
CrossOver(scores[selectIndex()].Item3,
scores[selectIndex()].Item3, breedingreate), pc, mutationrate);
var func = exp.Compile <Func <int, int, int> >(pc);
newpop.Add((func, exp));
}
else
{
//加入一个随机节点，增加种群的多样性
var exp = MakeRandomTree(pc);
var func = exp.Compile <Func <int, int, int> >(pc);
newpop.Add((func, exp));
}
}
population = newpop;
}
var printer = new GpPrinter();
_outputWriter?.Invoke(printer.Display(scores[0].Item3));
return(scores[0].Item2);
}
