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Student Perspective of GridWorld. Introduction. Roderick Baker, BSc (Hons). Computer Science. Thomas Randall, BSc (Hons). Cybernetics & Virtual Systems. Sean Wallace, BSc (Hons). Interactive Systems & Video Games Design. Synopsis. Development of AI agents for GridWorld.

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Presentation Transcript
introduction
Introduction
  • Roderick Baker, BSc (Hons). Computer Science.
  • Thomas Randall, BSc (Hons). Cybernetics & Virtual Systems.
  • Sean Wallace, BSc (Hons). Interactive Systems & Video Games Design.
synopsis
Synopsis
  • Development of AI agents for GridWorld.
  • The virtues of GridWorld.
  • Problems overcome in creating agents.
  • GridWorld as a learning tool.
  • Conclusion.
  • Questions.
visual studio net
Visual Studio.NET
  • Previous Experience.
  • Usefulness for Creating AI.
    • Simplifies Debugging.
  • Ease of use with GridWorld.
    • Allows the user to browse the API with ease and get the most out of it.
c the net platform
C# & The .NET Platform
  • Simple and intuitive language for all levels of developer.
  • Makes code simpler read and create.
    • Completely Object Orientated.
    • Has garbage collection.
  • .NET offered a lot of libraries easing the creation of game AI.
gridworld
GridWorld
  • Easy interface for creating game AI.
  • Allowed full control of the player(s) within game rules.
  • Offered functions to ease development.
  • Instant access to seeing the agent playing a game.
  • Replay files allowed students to view their agents progress and analyse errors.
gridworld7
GridWorld
  • Trace window allowed students to potentially view behaviour as it happened.
  • The client offered a local server so students could compare agents.
  • Online server results, allows students to compete and allows agents to gauge tactics.
problems
Problems
  • At the time GridWorld was still in development so some errors hindered creation.
    • We were effectively testers for the software.
  • Logical errors on our part.
  • Keeping CPU time below the allowed limit.
gridworld vs conventional teaching methods
GridWorld vs. Conventional Teaching Methods
  • GridWorld was fun:
    • To use, develop for, and to play.
    • Much more motivational and involving than other methods.
    • Almost instant reward for hard work.
  • GridWorld felt tailored for AI creation.
    • It allows developers to simplify difficult AI concepts.
conclusion
Conclusion
  • Introduction.
  • Development of AI agents for GridWorld.
  • The virtues of GridWorld.
  • Problems overcome in creating agents.
  • GridWorld as a learning tool.
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