why prolog is widely used for Artificial Intelligence?
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If you want a detailed answer, then I suggest you start here:\n\nhttp://www.google.co.uk/search?hl=en&q=prolog+AI&btnG=Google+Search&meta=\n\nRawlyn.
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To put the question in an operational way, you should first define what you mean as "self-awareness".\nSuppose tomorrow I give you a machine that I claim is self-aware. How do you plan to decide whether the machine is truly self-aware or is a fake?\nAlan Turing, in his famous paper of 1950 (see reference), proposed a simple test to decide that. The Turing test is still a reference framework for the AI.\n\nIf you accept (as I do) the rationale of the Turing test, your question is now well-posed.\nSaid that, my personal opinion is that there is no specific reason why a machine cannot pass the Turing test. It's only matter of time. Remember, some decades ago, Chess playing was considered the hard frontier of AI. Today you can get free or low-cost programs capable to win over most human Chess Masters.
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I think math is a convenient tool that can be used to facilitate operations in many other fields.\n\nIn computer science's programming, boolean algebra is used widely for logical operations. At the low machine level, native operations such as OR, XOR, NOT, etc are used to manipulate bits of information. At the high level, numerical analysis can be used to solve complex problems. Databases can use statistical methods to perform analysis.\n\nMath is an idealized (perfect) model that is coherent within itself. Hence it provides a very reliable framework for representation and modeling. Of course, the interpretation of the numbers is left to the more intelligent humans.\n\nComputer Science uses some aspects of Math. Math has alot more to offer.
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It costs money, but I find AI Roboform to be the most functional and easy to use.  I tried other free ones but they are not use friendly like Roboform. Spend the money it's woth it.
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Sorry but the model TI-83 is an outdated tool, that was used by the Aertms generation, six centuries ago.  This model could only perform 2,000 logic calculations per second.  In this age that is pathetic.  I am sorry all knowledge that is more then 2 centuries old has been deleted from my memory banks.
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Prolog or Lisp. Machine learning\nMore detail please.\nI'm more for Java.\nBut most likely you are looking for the toolkit From MATLAB(tm) the first link.
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I think you just need to go through this Wikipedia Page..\nIts really well maintained & with thorough explaination of various concepts..\nCheck: http://en.wikipedia.org/wiki/Portal:Artificial_intelligence
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Artificial Intellegence is a broad term that describes many programming techniques that mimic human thought. Things like expert systems, Alpha-Beta trees, and semantic networks.\n\nNeural Networks are formed from perceptrons that mimic a human neuron. So some inputs are fed to a perceptron and the perceptron weights them. If the output exceeds a threshold, the perceptron fires. The weights are the programming and there are ways to "learn" these weights from experience (for example, Hebb's learning rule). So neural networks can learn to read optical characters, for example, or play tic tac toe.\n\nOf course, AI can do the same thing, but AI techniques tend to be applied to more conventional programming techniques (how do we chain through rules, how do we examine the most number of game moves ahead). NN "learn" from training and experience how to get desired behaviors.
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Computers are lacking in their capability to learn. They tend to surpass humans in pure rationality issues, and eventually they'll be better at certain things humans are good at intuitively just by taking in enough information. However, the algorithms for a computer's intelligence requires everything to be objective. So there's no way for it to interpret something unless there's an algorithm there to determine how to interpret it. In short, the brain is self-programming. A computer does not really have that capability. To do such would require human beings knowing how to program computers that can program brains. And at that point, we might as well just program our own damned brains to be like that.\n\nBut in terms of raw processing speed, sure, computers will eventually surpass mankind. After all, if nothing else, they're likely using superior technology. All we have is a bunch of neurons and whatnot.
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well if your looking for books in logic, a book 'beginning logic' by Lemmon is a fantastic introduction, it goes from basic to fairly advanced Logic concepts
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absolutely! and i think thats a great question. i did not know about cyc or 20q.\n\ni could see this yahoo beta program here as something when properly utilized that could become the basis for sometihng 'smart'. and i dont just mean the answers to all of the questions, although those are certainly an integral part. i think that maybe what we are missing in our quest for artificial intelligence is that we are try to figure out how to get a machine to understand all of these facts and figures and answers.\n\ni think that we need to rethink things. what if we could teach a machine to ask questions?\n\nanyway, these are sortof the random musings that bounce around in my mind. good luck!
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There is no such thing. Artificial intelligence hasn't progressed enough to reliably mimic natural language understanding, much less understand and solve word problems. Looks like you're stuck doing your own homework.
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Yes, the definition for AI, when first coined, was broad enough that we can answer yes, AI has been made. We already have artificial intelligence, often referred to today as Weak AI, that performs relatively complex tasks. A good example is Deep Blue and other chess-playing programs. Other good examples are chatter bots. Most Weak AI, however, is created for the purpose of solving a specific solution or task. Games often implement a form of AI for enemies, using algorithms and previous user interactions to decide to throw a grenade, take cover, or shoot.\n\nIn contrast, Strong AI doe not yet exist. It is hard for a machine to prove, within human reason, that it has achived consciousness. There have been tests designed to indicate when Artificial Intelligence is really self-conscious, but there are questions that remain about whether those tests are sufficient enough to truly determine such a thing.
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Fuzzy Logic is very "stick it" powerful and effective control, but it often requires serious top-down engineering.\n\nWhat teaches itself is "Neural Networks", and they are very fast and effective.\n\nWhat the controls guys do is combine them to make "Neural-Fuzzy" Control.  It is self learning, very fast, and "sticks it" when nearly nothing else will.  Its awesome stuff.
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Intelligent systems or expert systems are grouped under the category of "Machine Learning" or in the fuzzy realm of AI.  \n\nAll of these systems are given a training set which allows them to callibrate on providing a particular action or judgment when presented with new data.  Using feedback loops these systems become better and better at determining the right answer (in effect they "learn").\n\nOne example of these systems is neural networks, highly connected systems that are "trained" to do certain tasks.  Your brain for instance is a very complicated neural network with thousands of nodes and billions of connections where the connections get stronger or weaker depending on your life learnings and experience.
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There are quite a few different languages in use for AI. any language will work for a start. Alice bot is a good start for anyone. It's based off of AIML, a new from of HTML for the program. It's easy to learn and they have alot of other information to other AI projects.
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Specific techniques for representing knowledge about products and processes, and for reasoning formally about them. \nhttp://www2.info.ucl.ac.be/research/projects/AVL/ReqEng.html