Skip to main content

Exiting a Maze

  • Chapter
  • First Online:
Agile Artificial Intelligence in Pharo
  • 637 Accesses

Abstract

Genetic algorithms are often presented as a way to solve a difficult algorithmic problem. This chapter applies a genetic algorithm to help a small robot find an exit. It formulates a simple situation (a robot looking for the exit) as an optimization problem (minimizing the distance between the robot and the exit). This chapter builds a small robot that lives in a randomly generated maze. The robot’s objective is to exit the maze.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 49.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 64.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Alexandre Bergel​

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Bergel, A. (2020). Exiting a Maze. In: Agile Artificial Intelligence in Pharo. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-5384-7_11

Download citation

Publish with us

Policies and ethics