使用生命游戏或其他虚拟环境进行人工（智能）生命模拟？
我对人工智能的兴趣之一不是集中在数据上，而是更多地集中在生物计算上。这包括神经网络、大脑映射、细胞自动机、虚拟生活和环境。
下面描述的是一个令人兴奋的项目，其中包括开发一个供机器人进化的虚拟环境。
“Polyworld 是一个由 Larry Yaeger 编写的跨平台（Linux、Mac OS X）程序，旨在通过自然选择和进化算法进化人工智能。” http://en.wikipedia.org/wiki/Polyworld "
Polyworld 是一个很有前途的项目研究虚拟生命，但它距离创建一个“智能自主”代理还很远，
理论上，你会使用什么参数来创建一个可能有自己的大脑环境？ 我想创建一个生命
模拟游戏，但不是一个网格，而是 N 个网格。网格是你的“生命力” 如果所有的生命实体都死在一个特定的网格中，那么整个网格就会死亡。
首先，我没有一个直接的目标。想要模拟一个环境并使用 OpenGL 可视化环境中发生的情况，并查看环境是否有任何有趣的属性。然后我想添加“稀缺资源”，看看人工智能环境是否能够充分管理资源。
One of my interests in AI focuses not so much on data but more on biologic computing. This includes neural networks, mapping the brain, cellular-automata, virtual life and environments.
Described below is an exciting project that includes develop a virtual environment for bots to evolve in.
"Polyworld is a cross-platform (Linux, Mac OS X) program written by Larry Yaeger to evolve Artificial Intelligence through natural selection and evolutionary algorithms."
http://en.wikipedia.org/wiki/Polyworld "
Polyworld is a promising project for studying virtual life but it still is far from creating an "intelligent autonomous" agent.
Here is my question, in theory, what parameters would you use create an AI environment? Possibly a brain environment? Possibly multiple self contained life organisms that have their own "brain" or life structures.
I would like a create a spin on the game of life simulation. What if you have a 64x64 game of life grid. But instead of one grid, you might have N number of grids. The N number of grids are your "life force" If all of the game of life entities die in a particular grid then that entire grid dies. A group of "grids" makes up a life form.
I don't have an immediate goal. First, I want to simulate an environment and visualize what is going on in the environment with OpenGL and see if there are any interesting properties to the environment. I then want to add "scarce resources" and see if the AI environment can manage resources adequately.
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既然你说“理论上”，那就意味着你有兴趣阅读大量有关该主题的学术论文，因为我认为那里有大量的理论工作，通常得到概念验证实验的支持。
我三年前上过一门关于这方面的课程，所以我的知识既是入门性的又是过时的，但尝试搜索类似 “神经网络语言演化”（Google 学术搜索*）。这些论文中的模拟应该能让您了解其他研究人员的尝试。然后，一个好的起点是复制您认为有趣的实验之一。
免责声明：我必须在课堂上这样做，这很糟糕。我决定我更喜欢工作程序而不是理论实验。但你说“理论上”，所以这可能是你真正喜欢的东西。
*抱歉，我记不清我们读过的具体论文了。
Since you said "in theory", that implies you are interested in reading a lot of academic papers on the subject, because I think there's plenty of theoretical work out there, usually supported by proof-of-concept experiments.
I took a class on this 3 years ago, so my knowledge is both introductory and out-of-date, but try searching for something like "neural network language evolution" on Google Scholar*. The simulations in those papers should give you some ideas of what other researchers have tried. Then, a good place to start is to replicate one of the experiments that you find interesting.
Disclaimer: I had to do just that for the class, and it sucked. I decided that I preferred working programs to theoretical experiments. But you said "in theory" so this might be the kind of thing you really like.
*Sorry, I can't remember the exact papers we read.