XMLANN Extensible Markup Language For Artificial Neural Network

What is your relationship with the Artificical Neurl Netwoks?

	I am Working in academic project.
	I know some informations about it.
	I have got interest about it.
	I'm Working with Real application Project.

What is XMLANN ?

XMLANN pronounced "ex-em-lan" a standard Extensible Markup Language for Artificial Neural Networks. Development, including all parts on work with topologies, Learning Algorithms Under training stage then testing stage, then use the out come Neural Network system in Real Applications. on parallel machines, PCs, Embedded systems, Robotics, and Electronic circuits.

This Framework can describe any Neural Networks, architectures, learning algorithms and run them under a simulator, then get them to the final stage, with many types of reports and figures.

Using XML language to mange all work in this project in the way witch make it easy to understand and have the management for Unix, Linux, and Windows operating systems, and embedded systems.

Why use XMLANN ?

We know that the Artificial Neural Networks is one grate science, and it has many descriptions, and implementations.

Every one describes Neural Networks only for there understanding, and have there own implementation code or circuits. So, we want to create standard description, and this description can apply for any ANN, Topology, Learning Algorithms, and run time using.

The latest technology of describing any thing is XML, but what is XML? The Extensible Markup Language (XML) is a simple, very flexible text format derived from SGML (ISO 8879). Originally designed to meet the challenges of large-scale electronic publishing, XML is also playing an increasingly important role in the exchange of a wide variety of data on the Web and elsewhere.

Most modern Frameworks like .NET and Java in Windows and KDE in Linux use the XML to describe projects and Compile or translate the Languages like C++, C# , Java, Basic to a specific version of XML, then tray to create the executable files.

So, here we have to set some standards format of XML Files, like main XML file of the project, and the training set file, Architecture Implement XML file, the Learning Algorithm XML file, and report files.

Using the Graphical Users Interface gives us the ability to edit the XML code and use the wizard to help developers finish there work in short time, using the most resent standard architecture, and the fastest implementations for a learning algorithm. at the top of that make sure that the same Neural Network designe can get better by updating the frame work or recompiling to deploy to target application.

This language is the standard interface for new way of working neural networks Under many platforms, machines, Robots, or real time applications.

Introduction
We have great promise of using Artificial Neural Networks (ANN) as a solution for present day robotics and for the future. Many robots have the ANN as an Artificial Intelligent Core.
A brief description of neural network, which can be used as an AI solution for robot evolution. Moreover, this essay notes the covered research in this point.
The essay is divided in to five sections. In section 1 I will give a short background to ANN and Robotics, which is very important for understanding the follower sections, in section 2, 3, 4 and 5 present some way of using ANN in robotics problems. In section 5 I discuss the robot and its learning task.