I am trying to read and understand the source of an existing C project. I keep feeling like it would be great to draw a UML Class Diagram for it to help me understand the high level relationships better, but of course - there are no classes to model.
Is there a formal diagram system that is used to model module relationships in a non-OO language? One that would be on a similar level of abstraction to a UML Class Diagram.
One alternative is to use Doxygen to map your function tree.
The OO paradigm is not a property of programming language and it's very possible to make OO implementation in C (just hard and not very intuitive). The OO design (in UML or any other modeling language) is not bound to a specific language.
Now let's get back to your question. There are many tools available for non-OO design. You can find a nice summary here and choose what fits you best.
Try FMC ( http://www.fmc-modeling.org/home) and "Apache Modelling Project" (Apache HTTP Sever modeled using FMC: http://www.fmc-modeling.org/projects/apache) as a starting point and guideline.
I'm looking for an Ada constructed framework for AI. I think Ada would be perfect for implementing temporal and stochastic paradigms due to its tasking and real-time mechanisms, but did not find anyone who tried to make such a libraries. Actually I did not find strong implementations on other languages too. For C# I found http://www.c-sharpcorner.com/1/56/, and for C++ I found http://mind.sourceforge.net/cpp.html but both did not get much popularity. Maybe java has good AI libraries too, but I do not know. So, do you know an Ada implementation? Would it be useful for more anyone? If you know libraries from other languages, it would be useful to know and compare the implementation models in java, for example. Thanks.
Here's a few resources:
Book, rather old, though (1989): Artificial Intelligence With Ada
Looks like some kind of university student dissertation: MUTANTS: A generic genetic algorithm toolkit for Ada 95
Dmitry Kazakov's AI stuff, mostly fuzzy logic. (Dmitry writes really nice software.)
I once had a school AI project that used the CLIPS AI builder library.
Since I avoid coding in C where I don't have to, I made an Ada Binding to it, which I believe is licensed without restriction. If you want it, have at.
I used it to build an expert system capable of playing a user's opening moves in Empire. All the code is either in Ada, or Clips' expert system specification language.
Here's a potentially useful Java library. I haven't heard of any Ada libraries. Ada is a great language, though.
Here's some genetic stuff.
The software's algorithms are all written in C.(gcc compiler). And I need some beautiful and friendly UI for this small software...But I have no idea what language and what library and what tool I should use.
I need some idea from you guys. thanks indeed!
If you can say it more specific, I will thank you more!
It would be better if you are more specific with your question and give more details about your software. Because designing a UI interface depends on a lot of factors.
I am listing some below for your reference:
On what system are people going to use it? (Windows, Linux etc)
Users are novice users or advanced users (You can decide on a CLI for advanced users and more detailed colourful GUI for novice users who need a lot of help)
Do you have any specific requirements like the GUI should be light weight?
So, please determine the requirements first before deciding what language and what library you must use.
For starters, you can look at ncurses library in linux, MFC in Windows. I don't know much about Java, someone else must be able to help you on that.
All the best for your work!
Commonly used libraries for GUIs:
Tk which was written in Tcl and has bindings for Python, Perl, Ruby, Lisp and a few others
GTK, which is written in C (so you could write your GUI in C) and has bindings for most languages under the sun
Qt, which is written in C++ and also has a number of bindings
These are the "big three" for cross-platform toolkits (I know some will disagree). They have their advantages and disadvantages: Tk looks good on some platforms but not others, and there aren't too many bindings for it, GTK looks great on Gnome desktops but so-so elsewhere, and Qt looks good in KDE but okay elsewhere.
You have to ask yourself a few questions: what platform will you be deploying to? What kind of functionality do you need? What languages are you most comfortable writing the interface with?
I'd recommend that whatever language you choose, choose a scripting language of some sort. It's far easier to create interfaces using scripting languages IMO (though Qt makes C++ interface design fairly painless). I'd also recommend you pick a language that will be available on your platform with as few dependencies as possible (so for Linux, Python or Perl would be a good choice).
I want to do RAD with C, but the only ones I can find only use C++.
Check out Glade, a UI designer for GTK+.
You may have to define what you expect when you use the term RAD. Technically is is a methodology agnostic of language (see http://en.wikipedia.org/wiki/Rapid_application_development, to understand what I mean).
If you mean "visual development" (which is the context in which it is applied to tools such as Delphi and C++Builder, primarily as marketing buzzwords and because Microsoft had already essentially trademarked "Visual" with respect to development tools), then use of C would require an application framework and tool to support this. There is a reason why such tools are usually implemented with object-oriented languages; it is a much more natural fit for GUI elements. This being the case, a tool vendor would be unlikely to choose C as the basis for such a tool.
Also it may be useful to understand what platform(s) you wish to target.
A judicious bit of Googling threw up a couple of things that may fit your requirements:
Auto-C
MGui
You may use BCX DevSuite Pro. It comes with GUI Designers that produces BCX code. When you compile BCX code, it produces also C code.
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What is the best programming language for artificial intelligence purposes?
Mind that using suggested language I must be able to employ any AI technique (or at least most of them).
All the cool bearded gurus in what's left of AI research use Lisp :)
There are two big camps: Common Lisp and Scheme. They have different syntax, etc. Lots of good stuff written for both.
Java is a very popular all-purpose language but a lot of the interesting stuff in AI / Functional Programming, such as passing closures as first-order objects, is clumsy to do in Java.
My personal preference would be to stay away from Windowsy languages like C# and F#. Cool people develop under Unix. Or Linux if they're cool but poor.
Some cool but weird people program in Haskell. A reasonably modern FP language with good performance. I tried it once, it made my brain hurt; but you might be smarter than I am.
UPDATE: Answers to Steve's questions.
I wouldn't be the one paying for a Unix variant; that's what corporations and research institutes do. The idea is, you want to be doing AI research for an outfit that sinks millions into their hardware and doesn't balk at paying a few thousand for an operating system. That's the kind of outfit likely to have good food in the cafeteria and/or pay well for doing fun work. But I'm certainly not knocking Linux.
F# may be cool but I see a whole raft of issues getting it to run on Linux or any other Unix (that's what I meant by "windowsy"), and I don't want to work under Windows (that's what I meant by "personal preference").
To elaborate on the "windowsy" theme: You mention that F# is an OCaml variant. From my own admittedly brief research, it seems that F# is missing functors, OCaml-style objects, polymorphic variants and the camlp4 preprocessor. A functional language without functors? Really? If one were disposed to not like Microsoft, as I admittedly am, one could conclude that they had gone ahead and crowbarred a perfectly good functional language, OCaml, into something they could get to run in their CLR so they could claim to "have" a functional language. Finally, because I don't suspect, I know that Microsoft always prioritizes market dominance over product quality, I don't plan to touch F#. But this is my personal preference, and clearly identified as such, while we're really more concerned with making a good recommendation for mary.ja45 .
I have better reasons to recommend Lisp over F# and even OCaml and Haskell. These are mostly based on the historic preponderance of Lisp over any other language in the AI field.
The bulk of AI literature is based on programs written in Lisp or Prolog. If nothing else, good knowledge of Lisp would allow a student to understand the sample programs. My personal favorite AI megaproject, Cyc, has runtimes in your choice of Common Lisp or C.
In the TIOBE index of programming language (as seen and used in industry), Lisp takes 15th place while Haskell takes 43rd and F# and OCaml place below 50th. Presence on the market correlates with employment opportunities, naturally.
That said, it's quite possible that a number of the younger "AI interesting" languages are poised to skyrocket. If some major research institute published some groundbreaking, defining-the-field research in, say, Scala, you'd see Scala's popularity advance sharply in the research community and, with some lag, in industry.
I (obviously) can't comment on F#'s other qualities but you're as welcome to make recommendations as I was.
Python seems to be used a lot in the general scientific community. It has a lot of libraries available and it's easy to learn.
I'll throw Scala into the pot.
it's usable for functional programming
it can be made as fast as Java
it's a modern language with lot's of nice aspects
Java seems to be a bit popular in AI, too and so you can use all those Java libraries from Scala
I've solved all exercises from a basic AI course in Scala. It worked really well.
If by "all of AI" you also mean machine learning, which I guess, Matlab, R and Python+Scipy should definately be mentioned.
I personally use Clojure for AI programming, and have found it to be a great all-rounder AI language.
Reasons:
It's a Lisp, and Lisps have historically been very strong the the AI field
It's a homoiconic language with powerful macros, so great for code generation and genetic programming. This is a surprisingly useful property for AI programming (and possibly explains some of the success of Lisp in general in this space)
It runs on the JVM and can easily access all the Java libraries for number crunching (Weka, Colt, etc.).
It's good for rapid interactive development - it's very dynamic and you can do pretty much everything interactively in a running Clojure REPL. No need for recompiling etc.
It matters probably whether the programming environment is academic or not, but for most non-academic AI application development I would recommend sticking with a mainstream language like Java or C++. One needs to be able to interface readily with other COTS or open-source software packages, and this can sometimes be difficult or impossible in more "exotic" languages. For academic work this may be a less critical issue.
Additionally, performance can be important for many applications, and mainstream languages generally have the most heavily-optimized compilers, e.g., C++ or Java.
It is true that functional programming languages like LISP, Scheme, etc have specialized features that may make it easier to implement particular AI methods, but I do not believe this to be true for AI-related programming as a whole, e.g., quantitative machine learning methods usually don't require a functional language. If you need access to both functional constructs and general software packages, there are some tools for LISP to help with this, and the recently-developed Clojure is a LISP-variant that runs on the JVM and can access Java libraries. Also, Groovy is another JVM-based language that includes support for closures.
Lastly, some programmers like paradigm flexibility and/or fast prototyping for AI projects. Ruby and Python both see some AI-related usage for this reason as multi-paradigm languages that can also be used for scripting.
Like most things in programming, the best answer for which language to use in AI development will ultimately depend on the needs of your projects.
It really depends on what kind of problem you are looking at. Also, how "deep" you want to go into AI stuff. If you want to learn from the basics and just implement theoretical AI stuff, go with a higher level language-- as in functional programming (and proven in AI) like lisp, or prolog. If you know what problem set you are dealing with and want efficient, go with something like Java, C++ and use a toolkit to do the stuff.
Since you mention Machine Learning look into Weka Toolkit in Java for some of these stuff.
Pick the programming language with AI techniques the same way you pick a language for any other project:
What is the problem you are trying to
solve?
Is there good support available for
the language?
What are the customers requirements?
I would recommend Prolog as a very good programming language used to implement AI systems.
There is no "best" language. Each one has its merits. When I studied AI, mostly we worked with lisp and prolog, but I've been most productive in AI with Java/C# and F# has a lot to offer.
How about a framework written in Java, supporting "High Level Logic" and agent style communication.
http://highlevellogic.blogspot.com/2010/11/when-will-we-have-artificial.html
It also depends on the size of your dataset. For web-scale datasets you may want to use Map-Reduce and that implies Hadoop. Hadoop is in Java -- but you could use any language (Python, etc.) for your Map-Reduce functions.
There is also a java framework called weka, developped by the university of waikato. I don't know wether it anwsers your question, but it may help.
Quoting wikipedia: «Weka supports several standard data mining tasks, more specifically, data preprocessing, clustering, classification, regression, visualization» and more.