Travelling Salesman
Compare the behavior of people in a maze with the differential evolution alg.
What's Travelling Salesman APK?
Travelling Salesman is a app for Android, It's developed by Michal Bukáček author.
First released on google play in 4 years ago and latest version released in 1 year ago.
This app has 76 download times on Google play
This product is an app in Board category. More infomartion of Travelling Salesman on google play
Scientific experiment: Compare the behavior of people in a maze with the differential evolution algorithm.
VSB - Technical University of Ostrava
The most common aim of computer game optimisation is to find the shortest path within a game or to solve a problem of a
travelling salesman within a small group of cities. This article deals with the possibilities of comparing the ascertained
solutions of a given problem of human intelligence and evolutionary algorithms. Human intelligence is represented by
mobile game players programmed for the Android operating system, by their conduct during playing the game, and by the
achieved results. Evolutionary algorithms are represented by differential evolution, where the best possible parameter
estimation will be sought based on the player’s results. This will provide results of a quality comparable to human players.
Another task is to verify whether this setting is suitable for all mazes and whether people or the differential evolution are
better at searching.
VSB - Technical University of Ostrava
The most common aim of computer game optimisation is to find the shortest path within a game or to solve a problem of a
travelling salesman within a small group of cities. This article deals with the possibilities of comparing the ascertained
solutions of a given problem of human intelligence and evolutionary algorithms. Human intelligence is represented by
mobile game players programmed for the Android operating system, by their conduct during playing the game, and by the
achieved results. Evolutionary algorithms are represented by differential evolution, where the best possible parameter
estimation will be sought based on the player’s results. This will provide results of a quality comparable to human players.
Another task is to verify whether this setting is suitable for all mazes and whether people or the differential evolution are
better at searching.
