Difference between revisions of "534: Genetic Algorithms"

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(Explanation: I clarified WHY the Skynet part should ALWAYS be part of a programme, but I do not really understand the maximize part. (Also, I am ignorant about Terminator.))
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In the computer science field of artificial intelligence, a genetic algorithm is a search heuristic that mimics the process of natural evolution. This heuristic is routinely used to generate useful solutions to optimization and search problems. Genetic algorithms belong to the larger class of evolutionary algorithms, which generate solutions to optimization problems using techniques inspired by natural evolution, such as inheritance, mutation, selection, and crossover.
 
In the computer science field of artificial intelligence, a genetic algorithm is a search heuristic that mimics the process of natural evolution. This heuristic is routinely used to generate useful solutions to optimization and search problems. Genetic algorithms belong to the larger class of evolutionary algorithms, which generate solutions to optimization problems using techniques inspired by natural evolution, such as inheritance, mutation, selection, and crossover.
  
The line indicated by an arrow is a reference to the Terminator series, in which the main antagonist is an artificial intelligence known as Skynet.
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The line indicated by an arrow is a reference to the Terminator series, in which the main antagonist is an artificial intelligence known as Skynet. By setting an absurdly high cost for an algorithm transforming into Skynet, the coder makes a preventative measure against the algorithm achieving such sentience.
  
 
The line about water crossing is a possible reference to the old computer game Oregon Trail, in which crossing water was hazardous.
 
The line about water crossing is a possible reference to the old computer game Oregon Trail, in which crossing water was hazardous.
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{{incomplete}}
  
 
==Transcript==
 
==Transcript==

Revision as of 14:45, 11 February 2013

Genetic Algorithms
Just make sure you don't have it maximize instead of minimize.
Title text: Just make sure you don't have it maximize instead of minimize.

Explanation

Cueball is seen here defining a program (possibly in python). The title is a reference to the type of program Cueball is writing, a Genetic Algorithm.

In the computer science field of artificial intelligence, a genetic algorithm is a search heuristic that mimics the process of natural evolution. This heuristic is routinely used to generate useful solutions to optimization and search problems. Genetic algorithms belong to the larger class of evolutionary algorithms, which generate solutions to optimization problems using techniques inspired by natural evolution, such as inheritance, mutation, selection, and crossover.

The line indicated by an arrow is a reference to the Terminator series, in which the main antagonist is an artificial intelligence known as Skynet. By setting an absurdly high cost for an algorithm transforming into Skynet, the coder makes a preventative measure against the algorithm achieving such sentience.

The line about water crossing is a possible reference to the old computer game Oregon Trail, in which crossing water was hazardous.


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Please include the reason why this explanation is incomplete, like this: {{incomplete|reason}}

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Transcript

[Code displayed, presumably from an IDE]
def getSolutionCosts(navigationCode):
fuelStopCost = 15
extraComputationCost = 8
[There is a giant arrow pointing to the next line]
thisAlgorithmBecomingSkynetCost = 999999999
waterCrossingCost = 45
Narration: Genetic algorithms tip: *Always* include this in your fitness function.


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Discussion

This solves the problem until you reach a situation where destroying all humans is outvalued by 22222 bridge crossings. Nafedalbi (talk) 15:53, 18 April 2022 (UTC)Nafedalbi

Could that be what Google Maps was trying to accomplish back when it had that "500 consecutive U-turns" bug?172.70.131.106 21:00, 18 April 2022 (UTC)