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In 2007 I created an open source computer vision project, ShapeLogic , built in Java to work with ImageJ . This setup has been very easy to work with and very productive. Bjarne Stroustrup the creator of C++ gave an interview about the new features in the C++ 0x standard and TR1 . http://blog.samibadawi.com/2008/09/computer-vision-c-vs-java-review.html

AI Computer Vision: Computer Vision C++ vs Java review

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neural network artificial intelligence java simulation software development en - Source Codes Search Engine - HackChina

http://code.google.com/p/marioai/

marioai - Mario AI Benchmark. AI and Machine Learning Experiments based on Super Mario Bros.

Experiments in applying evolutionary algorithms, neural networks and other AI/CI/ML algorithms to Super Mario Bros. MarioAI is a benchmark for machine learning and artificial intelligence based on Super Mario Bros. Check out the running Mario AI Championship 2010 at http://www.marioai.org !

Artificial Intelligence - Artificial Intelligence - Science - AllExperts.com

Chuck Cosby Top Expert on this page Expertise I can answer questions about speech recognition and natural language understanding. I am particulary strong in knowedge based natural langauge techniques. http://en.allexperts.com/q/Artificial-Intelligence-2506/
I would have to second the Perl / Python bit; they are both excellent languages for dealing with the Internet and processing data. Perl is arguably one of the most expressive languages ever made (if there is anything more expressive for general programming, it would probably have to be ASM or LISP). Python can often be used to produce maintainable code that also gets the job done painlessly, although the maintainability part depends on the monkey. Perl is however a huge language syntactically, and Python has many standard modules to choose from. http://www.daemonforums.org/showthread.php?t=2823

Java and AI-programming - DaemonForums

http://ai-depot.com/GameAI/Learning.html I n this article, I shall outline the current perceptions of 'Machine Learning' in the games industry, some of the techniques and implementations used in current and future games, and then explain how to go about designing your very own 'Learning Agent'. The Games Industry M achine Learning has been greeted with a certain amount of caution by games developers, and until recently, has not been used in any major games releases. Why is this -- surely there must be potential demand for games that can learn -- games that can adjust strategy to adapt to different opponents? There are several major reasons for the lack of enthusiasm which has, for a long time, been exhibited. Another question to be asked, is just how important is it for a game to 'learn'?

Machine Learning in Games Development

AI on the Web

http://aima.cs.berkeley.edu/ai.html This page links to 820 pages around the web with information on Artificial Intelligence. Links in Bold* followed by a star are especially useful and interesting sites. Links with a + sign at the end have "tooltip" information that will pop up if you put your mouse over the link for a second or two. If you have new links to add, mail them to peter@norvig.com . We hope you can find what you want in one of the following subtopics:
http://aima.cs.berkeley.edu/code.html The goal is to have working code for all the algorithms in the book in a variety of languages. So far, we have Java, Lisp and Python versions of most of the algorithms. There is also some old code in C++, C# and Prolog, but these are not being maintained.

Online Code Repository

DARPA Grand Challenge (2005)

http://en.wikipedia.org/wiki/DARPA_Grand_Challenge_%282005%29 The second driverless car competition of the DARPA Grand Challenge was a 212 km (132 mi) off-road course that began at 6:40am on October 8, 2005. All but one of the 23 finalists in the 2005 race surpassed the 11.78 km (7.32 mi) distance completed by the best vehicle in the 2004 race. Five vehicles successfully completed the course: Beer Bottle Pass Vehicles in the 2005 race passed through three narrow tunnels and navigated more than 100 sharp left and right turns. The race concluded through Beer Bottle Pass, a winding mountain pass with sheer drop-offs on both sides.
http://spectrum.ieee.org/automaton/robotics/artificial-intelligence/you-you-can-take-stanfords-intro-to-ai-course-next-quarter-for-free Stanford has been offering portions of its robotics coursework online for a few years now, but professors Sebastian Thrun and Peter Norvig are kicking things up a notch (okay, lots of notches) with next semester's CS221: Introduction to Artificial Intelligence . For the first time, you can take this course, along with several hundred Stanford undergrads, without having to fill out an application, pay tuition, or live in a dorm. This is more than just downloading materials and following along with a live stream; you're actually going to have to do all the same work as the Stanford students.

You (YOU!) Can Take Stanford's 'Intro to AI' Course Next Quarter, For Free

first learn basic mathematics. I keep getting asked this question and I keep saying the same thing - to three people in the last week, for e.g, two of whom were working through (or planning to work through) AIMA - so I thought I'd put this down here (and point anyone who asks the same question to this entry in the future). Learning AI (or any deep comp.sci for that matter) is not like learning J2EE or ruby "dsl"s or whatever the fad du jour in the enterprise software world is - read a few chapters of the latest bestselling "pragmatic" book, write some crappy web site and hey presto you are the expert. "Real" comp sci doesn't quite work like that. To understand a standard 3 layer feed forward neural network, for example, you need to have a solid grip on

To "learn AI"

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Artificial Intelligence

The Short: Researches across the globe are making daily advances towards the development of human level artificial intelligence, but sadly the algorithms and the software that represent these advances often remain hidden within researcher’s computer labs, out of reach for others to review and build upon. Enter OpenCog , an entire website dedicated to the development and distribution of artificial intelligence tools, software, and resources that are open source and freely available for anyone to use and modify.

Open Source Project Aims to Create Human Level Artificial Intelligence

SparkleShare – Un clone de Dropbox open source qui fonctionne !

Par Korben Bon on commence tôt ce matin, car j'ai enfin trouvé un remplaçant open source qui fonctionne et qui roxx à Dropbox ! Merci MrBoo ! L'outil s'appelle SparkleShare et va vous permettre enfin de synchroniser vos documents entre plusieurs ordinateurs, en utilisant votre propre serveur. Pour fonctionne SparkleShare a besoin d'un serveur Git.

Open Source AI projects

Further to this... I have an idea to create a new section called 'Resources' that will basically be a directory to open source (primarily) AI programming material. The notion is that members/visitors will be able to find active programming projects and source code for building AI systems and related projects. Any contributions to this end are welcome - ie, links, notification of current projects, state of projects, how to get involved etc etc.