Ant Colony Optimisation Algorithm

Try game asset Ant Colony Optimisation Algorithm 4.27 Unreal Engine for free.

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Game Assets
  • Platform

    Unreal Engine

  • Version

    4.27

  • Number

    105414

Description

The ant colony optimization algorithm (ACO) is a probabilistic technique for solving computational problems which can be reduced to finding good paths through graphs. Artificial ants stand for multi-agent methods inspired by the behavior of real ants. It helps to solve various tasks, including vehicle routing, internet routing [ Wiki ].

Finding an optimal path with brute force on the other hand would require a lot of computer power: (n-1)!/2 variant to compare, where n is the number of agents. For 15 points it would require to compare 43,589,145,600 paths.

With this plugin will be able to find the route for the same amount of points without notice.

Videos:

  • Finding an optimal path in changing environment using Ant Algorithm link ;
  • How changing obstacles affects path, calculated using Ant Algorithm link ;
  • Ant Algorithm in action for round objects on a moving platform: link ;
  • Ant Algorithm represents Eiffel Tower made of different paths: link ;
  • Ant Algorithm runtime path calculations for round objects link ;
  • Drawing a path with Ant Algorithm using the editor in Unreal Engine 4 link .

Technical Details

Features:

  • Finding an optimal path for actors in the scene;
  • Great for NPC's patrolling path automation;
  • Editing path in the editor with WYSIWYG concept;
  • Adapting path to moving targets;
  • Multithreaded calculations will not freeze the game thread;
  • Included Automation tests will help you to modify the solver for your needs if you want to.

Number of Blueprints: 1

Number of C++ Classes: 6

Network Replicated: No

Supported Platforms: Win64

Documentation: Tutorial

Example Project: 4.26 , 4.27

Notes: This plugin has limits on the size of the path it can solve. It was tested for 15 points with stable results.

Download

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  • Unreal Engine
    Platform
  • 4.27
    Version
  • 105414
    Number