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Inspired by Darwin's theory of evolution, bots that are evolved genetically to find path to the target.

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genobots

Visualize how genetic algorithm come to play while seeking a target.

A high-level description of algorithm given below

  1. Yellow rectangles are the Bots and magenta circle is the Target where we need all the bots to reach (eventually).
  2. A population of bots initially spawned without any sense of direction.
  3. In each generation, based on each bot's closeness to target (magenta circle) a fitness score is assigned to bots.
  4. Two bots in a generation is picked to reproduce next generation bot and each generation reproduces a new populatation for bots for next generation. Bots with higher fitness is set on higher probability to be picked for reproduction.
  5. One percent of time a mutation is introduced while reproducing the bot.
  6. Newly evolved bots continues to appear in each generation until a generation comes where all the bots learns to hits the target.

Try it yourself:

https://murlidharvarma.github.io/genobots

Hope you like it!

Preview

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Watch full end-to-end evolution below:

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Inspired by Darwin's theory of evolution, bots that are evolved genetically to find path to the target.

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