AI Director Analysis of Multi-agent Guiding

A Dissertation on Director Systems

  • Team Size: Solo Project
  • Role(s): Researcher & Programmer
  • Duration: 16 Weeks
  • Grade Achieved: 82% - First Class

    • My Dissertation for my Final Year Project at The University of Staffordshire was on "AI Director System for Multi Agent Guiding".
    This Dissertation acts as an overview of variety of AI technologies and asseses how they could be potentially be implemented alongside an AI Director system.
    The overall result of the implemented artefact did not prove or disprove a benefit/loss for a director system to be used to manage a group of AI. Despite the resulting artefact being unsuccessful, I have learned a wide variety of AI technologies and improved my Unreal Engine C++ skills to incorporate EQS systems and practiced the Type Object pattern as well as my blueprint skills.

    1 / 3
    AI Movement Tests
    2 / 3
    AI Hiding in Cover
    3 / 3
    AI Firing Tests

    Dissertation Link

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    AI Image
    AI Formation EQS Cover Query
    AI Image
    AI Formation Route
    AI Image
    AI Following Director Pawn
    AI Image
    AI Token Firing Tests

    Environment Query Systems

    For a section of my dissertation I discovered Environmental Query Systems for Unreal which allows for an agent in the world to search a range of points in the Environment and filter/score results based on test conditions.
    In Unreal Engine, these tests are simple to use and have a wide variety that are default in engine.

  • Navigable - Whether the agent can reach the point
  • Distance - How far the point is from the agent
  • Visibility - Can the agent see the point
  • Actor Type - Does it match a specific actor class
  • Overlapping - If the point in world is overlapping any actor

    • In the edge case I wanted to do, there was no directional querying, so I created a query generator which plotted data in a direction using a custom pyramid pattern.

    EnvQueryGenerator_Pyramid.cpp

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    Weapon Token System

    In the research conducted I found a token system designed for group firing by Sergio Ocio Barriales.
    He proposed that AI difficulty can be tweaked by altering the damage output of AI, I saw this and created an artefact that would use a token system for accuracy,
    similar to how the Ellie AI was created in TLOU
    The system would measure how many targets were percieving the player and vice versa to scale the number of successful shots that the AI can take, this would then be evaluated against a curve to determine a final token fire count value.
    Overall token systems for accuracy proved to work to a small degree, but to research further I would need to test with different values changing such as damage.

    AI Formations

    For the penultimate section of my artefact, a formation/cohesive movement was tested to determine whether the use of an AI Director could be used to create a cohesvie movement. Whilst the results of the formation and director follow were somewhat buggy, a director follow method was more consistent in results than a standalone system. In the Final section I combined all three artefact research areas to recieve a clear definition into whether it was a success, this was personally a failure due to the inability for the artefact to perform consistently,
    but overall the result came out as a 'maybe'. In the future a better implementation could be made to test these results better.

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