Newsflash: did you know that there's a secret strategy used by chess tournament masters that virtually guarantees them victory every time?

Or how about this: do you know which moves you should never, under any circumstances, make at the beginning of each game?

If you are a chess enthusiast, you owe it to yourself and to your opponent's to educate yourself on proper strategy and sequencing. Think about this -- how would you like to:

• Jump online and take on all comers with the same techniques the grandmasters use . . .
• Develop and OWN your personal variations to solid strategic moves . . .
• Crush your computer opponents and vault ahead through the levels of difficulty
• Stop being the whipping boy at the table . . .

Then you need to put some time in.

First, pick up this instruction set -- don't worry, it's dirt cheap and is packed with video and text. And then get to work, putting these strategies into action.

Good luck, and leave a comment here with your results so that we can all benefit!

You may know the name of the famous chess player Garry Kasparov who hit the highest rating in the history of FIDE at 2849. You may also know that the FIDE rating is calculated by the Elo system. But do you know how?The Elo system is named after Dr. Arpad Elo who improved the original one developed by Kenneth Harkness. It has been in use in the USA since 1960 and was taken on by FIDE in 1970. The system is twofold:

1. It shows how strong the player is: Player A rated 2400 is stronger than Player B rated 2300.
2. It also calculates the results of a game, tournament, or event as numerical Elo results.

Originally designed as a chess rating system, nowadays it is also being used in a number of other sports and computer games.Each chess player has chance to win a game. The stronger player, the more chances to win. FIDE uses a special winning probability table for a game which is based on the rating difference between the two opponents.

If the rating difference between the two is 0, each player has equal chances to win, and his or her winning probability is 0.50. If the difference is 100, the stronger player has the winning probability 0.64 while the weaker 0.36. Please remember 100, 0.64, and 0.36.Let's imagine that Player A rated 2400 and Player B rated 2300 are to officially play 100 games. The rating difference being 100, the expected result for Player A is therefore 0.64 and for Player B 0.36. And now the main idea... If Player A is really playing as strong as 2400 and Player B as 2300, at the end of the event Player A will score 64 and Player B 36 for sure. If Player A scores only 55 (but not expected 64) and Player B 45 (more than expected 36), the Elo system will change their new ratings.The system uses the K-factor which is necessary for rating calculation. The K-factor is assigned to the player, and its possible values in FIDE are 10, 15, and 25 as follows:
- 25 for players new to the rating list, until they have completed events with a total of at least 30 games.
- 15 for players with a rating under 2400.
- 10 once the player has reached 2400 and been registered for at least 30 games. Thereafter it remains permanently at 10, even if the player's rating is under 2400 at a later stage.The current rating of the chess player changes after each game. The one-game Rating Change depends on:
- The player's K-factor.
- The player's score (1, 0.5, or 0).
- The player's Expected Result for a game.Example 1. With the K-factor 10, Player A rated 2400 defeated Player B rated 2300.

The Rating Change for Player A is therefore calculated as this:
K-factor x (Result - Expected Result)
10 x (1 - 0.64) = 10 x 0.36 = 3.6

Example 2. With the K-factor 10, Player A rated 2400 lost to Player B rated 2300.
In this case, the Rating Change for Player A is calculated as this:
K-factor x (Result - Expected Result)
10 x ( 0 - 0.64) = 10 x (- 0.64) = - 6.4

Example 3. With the K-factor 10, Player A rated 2400 made a draw with Player B rated 2300.
The Rating Change for Player A is now calculated as this:
K-factor x (Result - Expected Result)
10 x (0.5 - 0.64) = 10 x (- 0.14) = - 1.4The new rating of the chess player is calculated based on the rating change. Updated, the FIDE rating list is available online on 1 January, 1 April, 1 July, and 1 October.

Bohdan Vovk is a chess supporter, and chess rating calculation is one of his hobbies. He runs a handful of websites and is the Author of an elo calculator program and some other products.

Article Source: http://EzineArticles.com/?expert=Bohdan_Vovk
http://EzineArticles.com/?Chess-Rating-Calculation-in-FIDE-(World-Chess-Federation)&id=1970613

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Fairyland Chess Set PiecesElves, fairies and pixies all cavort and dance in this charming Fairyland theme chess set! With breath-takingly pretty colors that are a perfect match for fairies, and delightful figures, you and everyone you know will delight in this set! The little folk of the forest tops and meadow lands are brought to life in this Fairyland chess set once more. Seeing them makes them seem so real you may take a walk and see them peering around the plants and trees!The elegant little knights are tiny pixies or fairies mounted on the miniature daring steeds, waiting to run as swift as the wind to their destination! One of the castles is a small mushroom, the proverbial home of the little folk. Resting under the mushrooms they wait for the rains and storms to subside before going on their merry way once again. The kings and queens both have their little pairs of wings, and seem ready to fly away from the board any moment! Delicate colors abound with every piece, and with everything together make the c

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Egyptian and Roman Chess Set PiecesEgyptian and Roman theme chess set! Did that catch your eye? Then this set will be a favorite. With the rulers of Egypt, their queens, commanders, and armies, you are all set for a pitched battle of the mind!A Caesar with his wife dominate the Roman side flanked by centurions, cavalry, and Roman towers, and protected on the front by the world-famous Roman legions. Is there anything that can spell defeat for the empire that once ruled the known world?A Pharoah and his wife, flanked by the vizier, the sun-god Ra, the renowned obelisks, and the protection in front of them composed of Egyptian spearmen are the basics of the army. Can the apparently weak Egyptians hold off the Roman attack? Or will Ra play a major part in the game and descend like a horse's hoof on the Roman army? That is up to you to discover!Specifications:Pieces: Non-weighted, hand-painted, plastic resin chessmen.King size: 3-1/4" tall, 1-1/8" bases.Pieces only. Chessboard not included.Set weighs 3 pounds.How

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Wildlife Animal Chess Set PiecesWith this African animals theme chess set, you just might get bitten! These pieces are so realistic that you'd better be careful when taking the opponents queen--you might lose a finger! Well, not quite that real, but this themed wildlife set is certainly a beauty to see and a joy to play.With weighted pieces and nicely sculptured wildlife resting on the base pedestals, you're sure to cruise to a victory with your elephants checkmating your opponents lion! Of course, you had better beware or you might lose yourself to a couple tall giraffes checkmating your own king from a distance. The wildlife add a very interesting turn to the usually straightforward chess game as we all know it.Specifications:Pieces: Single-weighted, plastic resin, hand painted.King size: 4" tall, 1-3/8" bases.Pieces only. Chessboard not included.Set weighs 6.25 pounds. How to choose a chessboard: Add one of our suggestions on this page or view Large Chess Boards and Storage Boxes (We recommend a

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Cats and Dogs Chess Set Pieces II (DISCONTINUED)You might not realize at first glance what you saw, and think that this was a European royalty theme chess set! For this Cats and Dogs set looks very official indeed. The cats have a blue theme to their uniforms and with their pristine appearance, appear to have just had a fresh manicure. As for the dogs, a distinct red color comes through their uniforms, giving a more outdoors look to their set-up, suiting them quite well.So, with the reds vs the blues, the dogs vs the cats, or the canines versus the felines, who will win? That's entirely up to you, either playing with the brains and claws or the brawn and bite on your side! However, it's very doubtful that these beautiful looking cats and dogs are going to wreck each others uniforms--instead, the game will probably be a plain and simple, 'gentleman's game'!This themed Cats and Dogs II chess set is made of non-weighted, plastic resin, hand painted chessmen.Specifications: King size: 3-1/4" tall, 1-1/8" bases.Pieces only. C

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When I lived in the Republic of China, the Chinese taught me how to play "syang chi" -- Chinese Chess. What an amazing game! 5,000 years old and still the best game around! Especially the short board version.

The Chinese actually have two versions, the long board, which is like our Chess, and the short board which is my favorite since a game can be played in 10 to 15 minutes.

This link explains the origins, the pieces and strategy.

To share this game with Americans, I used a label gun and ranked the pieces, and put each number ranking so that people can tell by the number.
(i.e, 1=king killer,
2J=the jumper,
3= horse,
4=chariot,
5=elephant,
6=warrior,
K=king).

I have other sets of the game that don't have the numbers on them which a lot of people enjoy playing.

If you find any great syanchi sites--or that better fit your needs, please email me at:
hunter621@yahoo.com

I have taught this game to dozens of people and they love it! I am a counselor and many of the teens had counseling--but I can teach them ancient game that no one else can comprehend and not only do the teens learn it quickly they accept me as a counselor!!

Hope you enjoy, rate, comment, subscribe if you want?

-James-

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f we compare our life style and requirements of the day with not more than 50 years back then one conclusion is obvious that we are evolved not merely in terms of knowledge but also in stance of requirements, needs and dependency over the external entities.

In short it can be said that as the domain of our knowledge expanded it also changed the scale of our dependency over the external entities, and to cop up with this dynamic world of knowledge one of the tools to assist came into being called “computers”.

There is very interesting thing related with computers.

Before the 1920s, computers were human clerks that performed computations. They were usually under the lead of a physicist. Many thousands of computers were employed in commerce, government and research establishment. Most of these computers were women and they were known to have a degree in calculus. Some performed astronomical calculations for calendars [1].

It gives us a clue of Artificial Intelligence. Clue is; most of the jobs that man was associated with, now machines are give the responsibility to perform, because machines can work on those things effortlessly. And it is said that if knowledge is the power then of course computer is an amplifier of this power. But we will see that now this domain of required knowledge is changing and know the definition of Knowledge in terms of computer is evolved from mindlessly performing some actions to reasoning and thinking and in this regard I am afraid computer is not a very good amplifier, yet.

If we broader our domain from computer system to the machines all around us then again it wont be unnatural or unusual, man has always manipulated the nature to cater its needs and these all mechanical development around us is a good piece of confirmation. Man maneuver the nature simply be the faculty of curiosity that is very much inherited by a child. When it opens its eyes, starts hearing voices, etc. You must have observed this phenomenon.

Computers can do many awesome things that are in the domain of computation but now man has again pushed its limits and challenged the nature in its endeavor of exploration.

For Aristotle, the most fascination aspect of nature was change. In his Physics, he defined his “ philosophy of nature” as the “ study of things that change “. [2]

Although there is no standard definition of Artificial Intelligence and many experts have suggested different definitions relevant to their work on it.

We can say that Artificial Intelligence is the study of intelligence that can be generated in the entities that do not inherit it. Although it is a definition by a student so do not solely reply on it.

INTELLIGENCE is something like fire, it is thought of a divine gift, randomly delivered in the form of lightning, forest fire or burning of lava. European peasants would insert a wooden frill in round hole and rotate it briskly between their palms to produce fire, Ancient Greeks used lenses or concave mirrors to concentrate the sun's rays and burning glasses were also used by Mexican Aztecs and the Chinese’s. Same is the case with Intelligence, chess playing and theorem-proving were thought as subject to intellect but now intelligent computers can defeat their masters in chess playing and even can have tremendous achievements at master level chess championships. Now it is quest of man to encage intelligence into the machines of iron and steel.

A more formal definition of Artificial Intelligence given by Elaine:

“ Artificial Intelligence is the study of how to make computers do things at which, at the moment, people are better”. [3]

So it is clear now that Artificial Intelligence is not the study to make computers efficient in what it can perform, already but it is a study of how to empower computers to do things at which at the moment people out class computers.

Computers are better than people in numerical computation, information storage, repetitive operation now what’s left, the core area of Artificial Intelligence i.e. Intelligent Behavior, even an ordinary person can perform better than a super computer. Dr. Seuss in her book writes that even the most super supercomputer lacks the reasoning capacity of a child engrossed. [4]

We do much more than just process information we understand it. We make sense out of what we see and hear; we use common sense to make our way through a world that sometimes seems highly illogical. [5]

So now our quest is streamlined but still there is a long way ahead to reach our destination. Before that do you know what intelligence is? Well most of us don’t or probably almost all of us.

But for the sake of abstract idea regarding intelligence I list some characteristic indispensable for an intelligence system, these characteristics are suggested by Douglas Hofstadter in a list of “essential abilities for Intelligence. He says for an intelligent system it needs:

· “To respond to situations very flexible”.

· “ To make sense out of ambiguous or contradictory messages”

· “To recognize the relative importance of different elements of a situation.”

· “To find similarities between situations despite differences which may separate them.”

· “To draw distinctions between situations despite similarities which may link them.”[6]

Mathematics can describe in great detail the technique for multiplying two numbers together because they can be described in intricate detail; computer performs them easily. On the other hand if an activity comes so naturally to you that you don’t have to think about it at all, you may have great difficult in describing exactly how you did it. What did you have for dinner last night?

Now, can you list the mental steps you went though to remember what you ate? [7]

And definitely learning is required to be intelligent. But when our computers are used-to with predefined instructions, when computer are already dictated what to do, how to do, and when to do, then is it learning. I don’t think so. Learning is basically reasoning and analyzing and in short concatenation new processed information to our already held knowledge database. Although, it is a big concern that how this knowledge need to be represented in computer system so that it can be retrieved for intelligent actions. One of the proposed actions taken by researchers is using Artificial Neural Networks. Those are closely resembled the human brain and activities taking place in it. And again it is very interesting thing that okay its fine computer ‘knows’ a lot of things but that’s what we know. How does computer know what it knows?

Another concern could be that why mimic human intelligence, when we all know that people don’t do things exact or optimal. Well the main reason to do so is this that we want our computers to perform activities sufficiently acceptable we don’t require them to be Intelligent and optimal at the same time although it is desired but just for a start it is not required. And to serve our energies to make computers Optimal and Intelligent, scientists are working over how to avoid “Artificial Stupidities”.

Following are the some research fields of Artificial Intelligence by John McCarthy [8]:

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.

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.

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.

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.

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.

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.

Right now it can be said that this field is evolving and still there is much more to be done. Currently, we have many questions but only some of them are answered. But being scientist we are not afraid to ask because question is the key to unlock the secrets of the nature.

I hope this preliminary introduction will give you better understanding about this field and its concerns.

“When the only tool you have is a hammer, every problem you encounter trends to resemble a nail”;

(Source – Unknown)

References:

1. wikipedia/History of computer science.

2. Artificial Intelligence, 3rd Edition. By George F. Luger and William A. Stubblefield, Page No. 65.

3. Understanding Artificial Intelligence by Henery C Mishkoff..

4. Herald Net. Published: Sunday, January 30, 2005. The A.I. equation.

5. Understanding Artificial Intelligence by Henery C Mishkoff.

6. An Eternal Golden Braid by Douglas Hofstadter. New York, vintage 1980, Page No. 6.

7. Understanding Artificial Intelligence by Henery C Mishkoff.

8. www-formal.stanford.edu/jmc/whatisai/whatisai.html