I m 寻找利用遗传算法来制定算法行为/决定战略的材料,而不是对准值。
我找不到很多东西。 请允许我向我指出正确的方向吗? 链接会很繁多,但我猜测一号是用搜索关键词、技术术语我不知道并且应该研究等等。
As Gordon Murray Dent说,如果利用革命方案来创造职能,则通常称为“基因方案”,而“遗传算法”通常是指(有些奇怪)功能参数优化。
The classic texts on genetic programming are Koza s books, which are still VERY relevant especially if you happen to be a LISP developer. His Website http://www.genetic-programming.com/ should give you plentiful leads for other resources.
http://en.wikipedia.org/wiki/Genetic_programming”rel=“nofollow”>genetic program。
Good thread on Google Answers about some algorithms Google answers
阿帕奇是一个名为Mahout/a。
"Machine learning algorithms" is a good keyword to search in google.
You can stick with optimization of pure parameters, yet obtain behaviors... Just evolve neural networks. For instance, a multi-layer Perceptron is able to approximate all functions. So evolve its parameters, such as the function it computes fullfill your objective. And tada, if you use a decent algorithm and don t have more than, say, 100 parameters, you might get something nice. Note that a neural network have real parameters, so use an evolutionary algorithm designed for real parameters. I suggest CMA-ES, not much tweaking necessary, the current benchmark winner & used in the real world.
I have a little problem in my little project , I wish that someone here could help me! I am planning to use a bayesian network as a decision factor in my game AI and I want to improve the decision ...
I would like to know what is a good, stable, framework that you guys suggest for implementing evolutionary optimisation techniques like PSO or GA? I have written my own ones and I like them, I would ...
If I have a network of nodes, how can I use genetic algorithms to calculate the shortest path between any two nodes?
让我想象一下,我有着一种不为人知的职能,我想通过转基因生物来估计。 在本案中,Ill假设为 y = 2x。
I m currently reading "Artificial Intelligence: A Modern Approach" (Russell+Norvig) and "Machine Learning" (Mitchell) - and trying to learn basics of AINN. In order to understand few basic things I ...
I m doing some work with Genetic Algorithms and want to write my own GA classes. Since a GA can have different ways of doing selection, mutation, cross-over, generating an initial population, ...
I am currently using Q-Learning to try to teach a bot how to move in a room filled with walls/obstacles. It must start in any place in the room and get to the goal state(this might be, to the tile ...
I tried this: float a = 1.4123; a = a & (1 << 3); I get a compiler error saying that the operand of & cannot be of type float. When I do: float a = 1.4123; a = (int)a & (1 <&...
