Computer Science Knowledge Sharing

Dr. Elmasri is Professor of Computer Science and Engineering at The University of Texas at Arlington. Dr. Elmasri received his B.S. in Electrical Engineering from Alexandria University, Egypt, in 1972. He completed his M.S. and Ph.D. degrees in Computer Science at Stanford University in 1980

CaptainSeeSharp

n mathematics, a ternary relation or triadic relation is a finitary relation in which the number of places in the relation is three. Ternary relations may also be referred to as 3-adic, 3-ary, 3-dimensional, or 3-place. Just as a binary relation is formally defined as a set of pairs, i.e. a subset of the Cartesian product A × B of some sets A and B, so a ternary relation is a set of triples, forming a subset of the Cartesian product A × B × C of three sets A, B and C.

COUNT(*) returns the number of items in a group. This includes NULL values and duplicates. COUNT(ALL expression) evaluates expression for each row in a group and returns the number of nonnull values. COUNT(DISTINCT expression) evaluates expression for each row in a group and returns the number of unique, nonnull values.

The Belief-Desire-Intention (BDI) software model (usually referred to simply, but ambiguously, as BDI) is a software model developed for programming intelligent agents. Superficially characterized by the implementation of an agent's beliefs, desires and intentions, it actually uses these concepts to solve a particular problem in agent programming. In essence, it provides a mechanism for separating the activity of selecting a plan (from a plan library) from the execution of currently active plans. Consequently, BDI agents are able to balance the time spent on deliberating about plans (choosing what to do) and executing those plans (doing it). A third activity, creating the plans in the first place (planning), is not within the scope of the model, and is left to the system designer and programmer.

object composition, which is often the best choice of all.

Familiarity with Microsoft Visual Basic 6.0

A Voyage to Functional Programming in F#

Finally I settled on F#. Both LISP and F# are belong to functional programming (FP) paradigm.Functional programming is a complete different paradigm from imperative (and OO) programming.I found it terse as well yet I can understand it (though some of the concepts are new to me).The advantage is it can use .NET Framework. Thus it gives me a break from OOP and yet taps the power from the familiar .NET Framework.Therefore I decided to dive into it to seem whether functional programming can deliver its claims in terms of productivity and expression power.I would like to share my findings in this blog to those interested in learning functional programming.

Deep Blue was a chess-playing computer developed by IBM. On May 11, 1997, the machine won a six-game match by two wins to one with three draws against world champion Garry Kasparov.[1] Kasparov accused IBM of cheating and demanded a rematch, but IBM declined and dismantled Deep Blue.[2] Kasparov had beaten a previous version of Deep Blue in 1996

Deep Blue was then heavily upgraded (unofficially nicknamed "Deeper Blue")[11] and played Kasparov again in May 1997, winning the six-game rematch 3½–2½, ending on May 11, finally ending in game six, and becoming the first computer system to defeat a reigning world champion in a match under standard chess tournament time controls.

The system derived its playing strength mainly out of brute force computing power.

design pattern is a widely accepted solution to a recurring design problem in OOP a design pattern describes how to structure classes to meet a given requirement provides a general blueprint to follow when implementing part of a program does not describe how to structure the entire application does not describe specific algorithms focuses on relationships between classes

design patterns: make you more productive help you write cleaner code Observer and Singleton are just two of the many available if you like design patterns, try these resources: GoF book -- Design Patterns: Elements of Reusable Object-oriented Software design pattern examples in Java, see Design Patterns in Java Reference and Example Site

learn what a design pattern is

In computer science, hill climbing is a mathematical optimization technique which belongs to the family of local search. It is relatively simple to implement, making it a popular first choice. Although more advanced algorithms may give better results, in some situations hill climbing works just as well. Hill climbing can be used to solve problems that have many solutions, some of which are better than others. It starts with a random (potentially poor) solution, and iteratively makes small changes to the solution, each time improving it a little. When the algorithm cannot see any improvement anymore, it terminates. Ideally, at that point the current solution is close to optimal, but it is not guaranteed that hill climbing will ever come close to the optimal solution. For example, hill climbing can be applied to the traveling salesman problem. It is easy to find a solution that visits all the cities but will be very poor compared to the optimal solution. The algorithm starts with such a solution and makes small improvements to it, such as switching the order in which two cities are visited. Eventually, a much better route is obtained. Hill climbing is used widely in artificial intelligence, for reaching a goal state from a starting node. Choice of next node and starting node can be varied to give a list of related algorithms.

The effect is named for the 1966 chatterbot ELIZA, developed by MIT computer scientist Joseph Weizenbaum

Dynamic programming problems are to be solved with tabular methods

breadth-first search

Memorize the value of pi You should always try to remember the value of pi as far as possible, 3.1415926535897932384626433832795, certainly the part in italics. The judges may not give the value in the question, and if you use values like 22/7 or 3.1416 or 3.142857, then it is very likely that some of the critical judge inputs will cause you to get the wrong answer. You can also get the value of pi as a compiler-defined constant or from the following code: Pi=2*acos(0)

Theory of mind is the ability to attribute mental states—beliefs, intents, desires, pretending, knowledge, etc.—to oneself and others and to understand that others have beliefs, desires and intentions that are different from one's own.[1]

One of the most important milestones in theory of mind development is gaining the ability to attribute false belief: that is, to recognize that others can have beliefs about the world that are wrong. To do this, it is suggested, one must understand how knowledge is formed, that people’s beliefs are based on their knowledge, that mental states can differ from reality, and that people’s behavior can be predicted by their mental states. Numerous versions of the false-belief task have been developed, based on the initial task done by Wimmer and Perner (1983).

In the most common version of the false-belief task (often called the ‘Sally-Anne’ task), children are told or shown a story involving two characters. For example, in one version, the child is shown two dolls, Sally and Anne, playing with a marble. The dolls put away the marble in a box, and then Sally leaves. Anne takes the marble out and plays with it again, and after she is done, puts it away in a different box. Sally returns and the child is then asked where Sally will look for the marble. The child passes the task if she answers that Sally will look in the first box where she put the marble; the child fails the task if she answers that Sally will look in the second box, where the child knows the marble is hidden, even though Sally cannot know, since she did not see it hidden there. In order to pass the task, the child must be able to understand that another’s mental representation of the situation is different from their own, and the child must be able to predict behavior based on that understanding. The results of research using false-belief tasks have been fairly consistent: most normally-developing children are unable to pass the tasks until around the age of three or four.

OpenGL (Open Graphics Library) is a standard specification defining a cross-language, cross-platform API for writing applications that produce 2D and 3D computer graphics. The interface consists of over 250 different function calls which can be used to draw complex three-dimensional scenes from simple primitives. OpenGL was developed by Silicon Graphics Inc. (SGI) in 1992[1] and is widely used in CAD, virtual reality, scientific visualization, information visualization, and flight simulation. It is also used in video games, where it competes with Direct3D on Microsoft Windows platforms (see Direct3D vs. OpenGL). OpenGL is managed by the non-profit technology consortium, the Khronos Group.

Mark Segal and Kurt Akeley authored the original OpenGL specification

These headers tell us which web server you were trying to contact.  If that seems odd, bear in mind that many web sites can be "hosted" on a single server, so when the request is received it needs to know which web site you were attempting to access

The request method is usually either "GET" or "POST".  Basically if you fill in and submit a form on a web page it might generate a POST request (or it might be "GET"), whereas if you just click on a link, or activate one of your browser's "bookmarks" or "favourites", then the request method will always be "GET". Therefore, if it's "POST", we can tell that a form was definitely submitted.  The contents of the form would appear here, and there would also be some "Content-" headers describing the data. Web browsers generate two kinds of "POST" data: either "multipart/form-data", which is used when uploading files to a web server, or the more common "application/x-www-form-urlencoded".

The "referer" header tells us which document referred you to us - in essence, if you followed a link to get to this page, it is the URL of the page you came from to get here.

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