IMEC Conceptual Model

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IMEC Conceptual Model

• Matthew Rabiee
• Jonathan Russell
• Justin Smith

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Abstract

• We are to design an application to interact with
  Dr. Dozier's genetic algorithm. This application
  is to be on individual machines that interact,
  through the internet, with a server. This server
  will have a Meme space and the genetic algorithm
  running on it. The application will display the
  non-dominating solutions to the scientists and
  allow them to select coordinates of the preferred
  solutions.

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Task Analysis

• Select Individuals
• Deselect Individuals
• Sort Individuals by a Function
• Unsort Individuals
• Reorder Functions
• Hide Functions
• Unhide Functions
• Submit Selected Individuals

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Lexicon

• Genetic Algorithm -An evolutionary algorithm
  which generates each individual from some encoded
  form known as a "chromosome" or "genome".
  Chromosomes are combined or mutated to breed new
  individuals. "Crossover", the kind of
  recombination of chromosomes found in sexual
  reproduction in nature, is often also used in
  GAs. Here, an offspring's chromosome is created
  by joining segments choosen alternately from each
  of two parents' chromosomes which are of fixed
  length.
• Meme Space - Memes are contagious ideas, all
  competing for a share of our mind in a kind of
  Darwinian selection. As memes evolve, they become
  better and better at distracting and diverting us
  from whatever we'd really like to be doing with
  our lives. They are a kind of Drug of the Mind.
• Non-dominating Solution - A plan non-dominated if
  no other single plan has been found which is
  better in all objectives.
• Pareto Front A collection of non-dominating
  solutions.

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Task Scenario

• A NASA scientist is needed to select
  non-dominated solutions that are generated by a
  Genetic Algorithm. He needs an application that
  will allow him to visualize the data to make
  better decisions on which solutions are preferred.

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