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What is Domain Name Resolution Introduction When using the Internet most people connect to web sites, ftp servers or other Internet servers by connecting to a domain name, as in www.bleepingcomputer.com. Internet applications, though, do not communicate via domain names, but rather using IP addresses, such as 192.168.1.1. Therefore when you type a domain name in your program that you wish to connect to, your application must first convert it to an IP address that it will use to connect to. The way these hostnames are resolved to their mapped IP address is called Domain Name Resolution. On almost all operating systems whether they be Apple, Linux, Unix, Netware, or Windows the majority of resolutions from domain names to IP addresses are done through a procedure called DNS.

Hosts File - There is a file called the HOSTS file that you can use to convert domain names to IP addresses. Entries in the HOSTS file override any mappings that would be resolved via a DNS server

Netbios - This only applies to Windows machines and will only be used to map names to IP addresses if all previous methods failed. This method will attempt to map the netbios name you are trying to connect to with an IP address.

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.

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.