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This is not an encyclopedia article. If you find this page on any site other than Wikipedia, you are viewing a mirror site. Be aware that the page may be outdated and that the user this page belongs to may have no personal affiliation with any site other than Wikipedia itself. The original page is located at http://en.wikipedia.org/wiki/User:DGwarez.
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This is ME!
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This user plays football with hands only when tending goals. |
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This user was born on February 17. |
But anyway,
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This user can program in C++. |
Got problems with calculus?
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This user drinks tea. |
Template:User USA-India
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This user rejects all forms of Marxist thinking. |
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This user is a committed advocate of democracy. |
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[edit] About Me
I am an 18 year old Bengali staying at Kolkata, West Bengal, India. Right now, I'm a first year Information Technology student in C.I.E.M, Tollygunge, near Kolkata. My e-mail address is avik_d2000@yahoo.co.in. I like discussing topics on nuclear and modern physics(relativity, string theories etc.). From the maths part, I am sort of OK in Calculus. My favorite topics of Mathematics are Probability theory and Permutation/Combinations. I am trying to collect materials from various books to write a good article on definite Integrals(in Wikipedia of course!). I love computers and computer related gadgets. I can program in C++, but I'm not an expert. I have basic knowledge of Oracle, Java and HTML programming. I can crack and reverse engineer softwares but I do that just for fun. I DO NOT support piracy. I love playing computer games. Especially Grand Theft Auto games. Unfortunately San Andreas won't work on my computer. I am a big fan of Satyajit Ray's literary works. Especially Professor Shanku. Currently I am working on articles related to Mathematics, Physics, Computers, India and Satyajit Ray.
[edit] And Finally!!!
Check out the userboxes on the right side of the page. They should tell you a lot more about me.
I am a new wikipedian and if I make any mistake please feel free to inform me about it. I have uploaded a few images but I don't understand this copyright issue very well. I am interested in astronomy and I like to read about stars & planets. NOTE: - My topics of interest change very often so watch this section for more info.
[edit] Current Topic of Interest
Pluto, Pluto, Pluto, art thou a planet?
[edit] 'Dwarf' Pluto
Pluto orbits beyond the orbit of Neptune (usually). It is much smaller than any of the official planets and now classified as a "dwarf planet". Pluto is smaller than seven of the solar system's moons (the Moon, Io, Europa, Ganymede, Callisto, Titan and Triton).
orbit: 5,913,520,000 km (39.5 AU) from the Sun (average)
diameter: 2274 km
mass: 1.27e22 kg
In Roman mythology, Pluto (Greek: Hades) is the god of the underworld. The planet received this name (after many other suggestions) perhaps because it's so far from the Sun that it is in perpetual darkness and perhaps because "PL" are the initials of Percival Lowell.
Pluto was discovered in 1930 by a fortunate accident. Calculations which later turned out to be in error had predicted a planet beyond Neptune, based on the motions of Uranus and Neptune. Not knowing of the error, Clyde W. Tombaugh at Lowell Observatory in Arizona did a very careful sky survey which turned up Pluto anyway.
After the discovery of Pluto, it was quickly determined that Pluto was too small to account for the discrepancies in the orbits of the other planets. The search for Planet X continued but nothing was found. Nor is it likely that it ever will be: the discrepancies vanish if the mass of Neptune determined from the Voyager 2 encounter with Neptune is used. There is no Planet X. But that doesn't mean there aren't other objects out there, only that there isn't a relatively large and close one like Planet X was assumed to be. In fact, we now know that there are a very large number of small objects in the Kuiper Belt beyond the orbit of Neptune, some roughly the same size as Pluto.
There has recently been considerable controversy about the classification of Pluto. It was classified as the ninth planet shortly after its discovery and remained so for 75 years. But on 2006 Aug 24 the IAU decided on a new definition of "planet" which does not include Pluto. Pluto is now classified as a "dwarf planet", a class distict from "planet". While this may be controversial at first (and certainly causes confusion for the name of this website) it is my hope that this ends the essentially empty debate about Pluto's status so that we can get on with the real science of figuring out its physical nature and history.
[edit] Branches of AI
Q. What are the branches of AI?
A. Here's a list, but some branches are surely missing, because no-one has identified them yet. Some of these may be regarded as concepts or topics rather than full branches.
Logical AI What a program knows about the world in general the facts of the specific situation in which it must act, and its goals are all represented by sentences of some mathematical logical language. The program decides what to do by inferring that certain actions are appropriate for achieving its goals. The first article proposing this was [McC59]. [McC89] is a more recent summary. [McC96b] lists some of the concepts involved in logical aI. [Sha97] is an important text.
Search AI programs often examine large numbers of possibilities, e.g. moves in a chess game or inferences by a theorem proving program. Discoveries are continually made about how to do this more efficiently in various domains.
Pattern recognition When a program makes observations of some kind, it is often programmed to compare what it sees with a pattern. For example, a vision program may try to match a pattern of eyes and a nose in a scene in order to find a face. More complex patterns, e.g. in a natural language text, in a chess position, or in the history of some event are also studied. These more complex patterns require quite different methods than do the simple patterns that have been studied the most.
Representation Facts about the world have to be represented in some way. Usually languages of mathematical logic are used.
Inference From some facts, others can be inferred. Mathematical logical deduction is adequate for some purposes, but new methods of non-monotonic inference have been added to logic since the 1970s. The simplest kind of non-monotonic reasoning is default reasoning in which a conclusion is to be inferred by default, but the conclusion can be withdrawn if there is evidence to the contrary. For example, when we hear of a bird, we man infer that it can fly, but this conclusion can be reversed when we hear that it is a penguin. It is the possibility that a conclusion may have to be withdrawn that constitutes the non-monotonic character of the reasoning. Ordinary logical reasoning is monotonic in that the set of conclusions that can the drawn from a set of premises is a monotonic increasing function of the premises. Circumscription is another form of non-monotonic reasoning.
Common sense knowledge and reasoning This is the area in which AI is farthest from human-level, in spite of the fact that it has been an active research area since the 1950s. While there has been considerable progress, e.g. in developing systems of non-monotonic reasoning and theories of action, yet more new ideas are needed. The Cyc system contains a large but spotty collection of common sense facts.
Learning from experience Programs do that. The approaches to AI based on connectionism and neural nets specialize in that. There is also learning of laws expressed in logic. [Mit97] is a comprehensive undergraduate text on machine learning. Programs can only learn what facts or behaviors their formalisms can represent, and unfortunately learning systems are almost all based on very limited abilities to represent information.
Planning Planning programs start with general facts about the world (especially facts about the effects of actions), facts about the particular situation and a statement of a goal. From these, they generate a strategy for achieving the goal. In the most common cases, the strategy is just a sequence of actions.
Epistemology This is a study of the kinds of knowledge that are required for solving problems in the world.
Ontology Ontology is the study of the kinds of things that exist. In AI, the programs and sentences deal with various kinds of objects, and we study what these kinds are and what their basic properties are. Emphasis on ontology begins in the 1990s.
Heuristics A heuristic is a way of trying to discover something or an idea imbedded in a program. The term is used variously in AI. Heuristic functions are used in some approaches to search to measure how far a node in a search tree seems to be from a goal. Heuristic predicates that compare two nodes in a search tree to see if one is better than the other, i.e. constitutes an advance toward the goal, may be more useful. [My opinion].
Genetic programming Genetic programming is a technique for getting programs to solve a task by mating random Lisp programs and selecting fittest in millions of generations. It is being developed by John Koza's group and here's a tutorial.
