Group items tagged

IPv4 Internet Protocol version 4

IPv6 Internet Protocol version 6

TCP Transmission Control Protocol UDP User Datagram Protocol

The Common Gateway Interface (CGI) is a standard protocol for interfacing external application software with an information server, commonly a web server. The task of such an information server is to respond to requests (in the case of web servers, requests from client web browsers) by returning output. Each time a request is received, the server analyzes what the request asks for, and returns the appropriate output. The two basic methods for the server to do this are the following: If the request identifies a file stored on disk, then return the contents of that file. If the request identifies an executable command and possibly arguments, then run the command and return its output. CGI defines a standard way of doing the second. It defines how information about the server and the request is passed to the command in the form of arguments and environment variables, and how the command can pass back extra information about the output (such as the type) in the form of headers.

A production system (or production rule system) is a computer program typically used to provide some form of artificial intelligence, which consists primarily of a set of rules about behavior. These rules, termed productions, are a basic representation found useful in AI planning, expert systems and action selection. A production system provides the mechanism necessary to execute productions in order to achieve some goal for the system. Productions consist of two parts: a sensory precondition (or "IF" statement) and an action (or "THEN"). If a production's precondition matches the current state of the world, then the production is said to be triggered. If a production's action is executed, it is said to have fired. A production system also contains a database, sometimes called working memory, which maintains data about current state or knowledge, and a rule interpreter. The rule interpreter must provide a mechanism for prioritizing productions when more than one is triggered.

A production system (or production rule system) is a computer program typically used to provide some form of artificial intelligence, which consists primarily of a set of rules about behavior. These rules, termed productions, are a basic representation found useful in AI planning, expert systems and action selection. A production system provides the mechanism necessary to execute productions in order to achieve some goal for the system. Productions consist of two parts: a sensory precondition (or "IF" statement) and an action (or "THEN"). If a production's precondition matches the current state of the world, then the production is said to be triggered. If a production's action is executed, it is said to have fired. A production system also contains a database, sometimes called working memory, which maintains data about current state or knowledge, and a rule interpreter. The rule interpreter must provide a mechanism for prioritizing productions when more than one is triggered.

In computing, a Uniform Resource Identifier (URI) consists of a string of characters used to identify or name a resource on the Internet. Such identification enables interaction with representations of the resource over a network (typically the World Wide Web) using specific protocols. Schemes specifying a specific syntax and associated protocols define each URI. Contents [hide]

A Uniform Resource Name (URN) functions like a person's name, while a Uniform Resource Locator (URL) resembles that person's street address. The URN defines an item's identity, while the URL provides a method for finding it. The ISBN system for uniquely identifying books provides a typical example of the use of typical URNs. ISBN 0486275574 (urn:isbn:0-486-27557-4) cites unambiguously a specific edition of Shakespeare's play Romeo and Juliet. In order to gain access to this object and read the book, one would need its location: a URL address. A typical URL for this book on a unix-like operating system might look like the file path file:///home/username/RomeoAndJuliet.pdf, identifying the electronic book saved in a local hard disk. So URNs and URLs have complementary purposes.

In telecommunications and software engineering, scalability is a desirable property of a system, a network, or a process, which indicates its ability to either handle growing amounts of work in a graceful manner, or to be readily enlarged.[1] For example, it can refer to the capability of a system to increase total throughput under an increased load when resources (typically hardware) are added. An analogous meaning is implied when the word is used in a commercial context, where scalability of a company implies that the underlying business model offers the potential for economic growth within the company.

A genetic algorithm (GA) is a search technique used in computing to find exact or approximate solutions to optimization and search problems. Genetic algorithms are categorized as global search heuristics. Genetic algorithms are a particular class of evolutionary algorithms (EA) that use techniques inspired by evolutionary biology such as inheritance, mutation, selection, and crossover (also called recombination).

A typical genetic algorithm requires: a genetic representation of the solution domain, a fitness function to evaluate the solution domain.

Neuroplasticity (also referred to as brain plasticity, cortical plasticity or cortical re-mapping) is the changing of neurons and the organization of their networks and so their function by experience. This idea was first proposed in 1892 by Santiago Ramón y Cajal the proposer of the neuron doctrine though the idea was largely neglected for the next fifty years.[1] The first person to use the term neural plasticity appears to have been the Polish neuroscientist Jerzy Konorski.[2]

SOAP, originally defined as Simple Object Access Protocol, is a protocol specification for exchanging structured information in the implementation of Web Services in computer networks. It relies on Extensible Markup Language (XML) as its message format, and usually relies on other Application Layer protocols (most notably Remote Procedure Call (RPC) and HTTP) for message negotiation and transmission. SOAP can form the foundation layer of a web services protocol stack, providing a basic messaging framework upon which web services can be built.

Rich Internet applications (RIAs) are web applications that have some of the characteristics of desktop applications, typically delivered by way of a proprietary web browser plug-ins or independently via sandboxes or virtual machines[1]. Examples of RIA frameworks include Curl (programming language), Adobe Flash/Adobe Flex/AIR, Java/JavaFX[2], uniPaaS[3] and Microsoft Silverlight[4].

A pattern must explain why a particular situation causes problems, and why the proposed solution is considered a good one. Christopher Alexander describes common design problems as arising from "conflicting forces" -- such as the conflict between wanting a room to be sunny and wanting it not to overheat on summer afternoons. A pattern would not tell the designer how many windows to put in the room; instead, it would propose a set of values to guide the designer toward a decision that is best for their particular application. Alexander, for example, suggests that enough windows should be included to direct light all around the room. He considers this a good solution because he believes it increases the enjoyment of the room by its occupants. Other authors might come to different conclusions, if they place higher value on heating costs, or material costs. These values, used by the pattern's author to determine which solution is "best", must also be documented within the pattern. A pattern must also explain when it is applicable. Since two houses may be very different from one another, a design pattern for houses must be broad enough to apply to both of them, but not so vague that it doesn't help the designer make decisions. The range of situations in which a pattern can be used is called its context. Some examples might be "all houses", "all two-story houses", or "all places where people spend time." The context must be documented within the pattern. For instance, in Christopher Alexander's work, bus stops and waiting rooms in a surgery are both part of the context for the pattern "A PLACE TO WAIT."

OL (also written with some or all letters lowercase) is an abbreviation for laughing out loud[1][2] or laugh out loud.[3] LOL is a common element of Internet slang used historically on Usenet, but now widespread in other forms of computer-mediated communication, and even face-to-face communication. It is one of many initialisms for expressing bodily reactions, in particular laughter, as text, including initialisms such as ROTFL[4][5][6][7] or ROFL [8] ("roll(ing) on the floor laughing"), a more emphatic expression of laughter, and BWL ("bursting with laughter"), above which there is "no greater compliment" according to technology columnist Larry Magid.[9] Other unrelated expansions include the now mostly historical "lots of luck" or "lots of love" used in letter-writing.[10

Corruptions of "LOL"

An Abstract Agent Programming Language or Artificial Autonomous Agents Programming Language or 3APL (pronounced triple-A-P-L) is an experimental tool and programming language for the development, implementation and testing of multiple cognitive agents using the Belief-Desire-Intention (BDI) approach. The newest incarnation of 3APL is 2APL (A Practical Agent Programming Language).

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.

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.

CaptainSeeSharp

Model–view–controller (MVC) is an architectural pattern used in software engineering. Successful use of the pattern isolates business logic from user interface considerations, resulting in an application where it is easier to modify either the visual appearance of the application or the underlying business rules without affecting the other. In MVC, the model represents the information (the data) of the application; the view corresponds to elements of the user interface such as text, checkbox items, and so forth; and the controller manages the communication of data and the business rules used to manipulate the data to and from the model.

MVC is often seen in web applications, where the view is the actual HTML or XHTML page, and the controller is the code that gathers dynamic data and generates the content within the HTML or XHTML. Finally, the model is represented by the actual content, which is often stored in a database or in XML nodes, and the business rules that transform that content based on user actions.

Flocking behavior is the behavior exhibited when a group of birds, called a flock, are foraging or in flight. There are parallels with the shoaling behavior of fish, or the swarming behavior of insects. Computer simulations and mathematical models which have been developed to emulate the flocking behaviors of birds can generally be applied also to the "flocking" behavior of other species. As a result, the term "flocking" is sometimes applied, in computer science, to species other than birds. This article is about the modelling of flocking behavior. From the perceptive of the mathematical modeller, "flocking" is the collective motion of a large number of self-propelled entities and is a collective animal behavior exhibited by many living beings such as birds, fish, bacteria, and insects.[1] It is considered an emergent behaviour arising from simple rules that are followed by individuals and does not involve any central coordination. Flocking behavior was first simulated on a computer in 1986 by Craig Reynolds with his simulation program, Boids. This program simulates simple agents (boids) that are allowed to move according to a set of basic rules. The result is akin to a flock of birds, a school of fish, or a swarm of insects.

Flocking behavior is the behavior exhibited when a group of birds, called a flock, are foraging or in flight. There are parallels with the shoaling behavior of fish, or the swarming behavior of insects. Computer simulations and mathematical models which have been developed to emulate the flocking behaviors of birds can generally be applied also to the "flocking" behavior of other species. As a result, the term "flocking" is sometimes applied, in computer science, to species other than birds. This article is about the modelling of flocking behavior. From the perceptive of the mathematical modeller, "flocking" is the collective motion of a large number of self-propelled entities and is a collective animal behavior exhibited by many living beings such as birds, fish, bacteria, and insects.[1] It is considered an emergent behaviour arising from simple rules that are followed by individuals and does not involve any central coordination. Flocking behavior was first simulated on a computer in 1986 by Craig Reynolds with his simulation program, Boids. This program simulates simple agents (boids) that are allowed to move according to a set of basic rules. The result is akin to a flock of birds, a school of fish, or a swarm of insects.

A system in a steady state has numerous properties that are unchanging in time. The concept of steady state has relevance in many fields, in particular thermodynamics. Steady state is a more general situation than dynamic equilibrium. If a system is in steady state, then the recently observed behavior of the system will continue into the future. In stochastic systems, the probabilities that various different states will be repeated will remain constant.

The Belief-Desire-Intention (BDI) model of human practical reasoning was developed by Michael Bratman as a way of explaining future-directed intention. BDI is fundamentally reliant on folk psychology (the 'theory theory'), which is the notion that our mental models of the world are theories.