About Grail

GRAIL: Advanced Intelligent Behaviors in Games

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• Grail for Developers

  If you are a developer you will find that using Grail you can implement typical decision-making AI faster and easier. You will achieve sophistication that would be infeasible to create from scratch. Grail offers tools to define not only the behavior of computer agents (building blocks for game AI) but also parameterizable and reusable decision-making systems for them (with algorithms such as Utility AI, Planning, Monte Carlo Tree Search running under the hood). Additionally, you will work with easy to use and well documented interfaces for the techniques.

  Where else could Grail be a support to you? In preparation of a multi-agent system, in which agents communicate with each other using a black-board architecture or in configuring the created AI system using GUI-based tools. In many parts, there is also no coding needed, so the configuration can be partly done by designers. Grail can also be used to debug and analyze the created AI system using GUI-based tools. You can use Grail in one of four forms: a native C++ library, a native C# library, an Unreal Engine 4 plugin or a Unity3D plugin.

• Grail for non-experts

  Grail is about implementing decision-making. It is a tool for developers and designers who work in this area. To help your product make incredibly smart decisions. You can use two sides of Grail. The design-based side helps your virtual characters do certain things you want them to do in your video games, virtual reality tutorials, 3D/CG movies. The procedural side enables your agents to reason about goals (after the developers provide a model of the game reality).

  Using Grail the programmers are able to implement the desired behavior faster, without the need of profound understanding of the algorithms (a basic one is required, though). Thanks to the procedural techniques, the behavior can also be more sophisticated if needed. Meaning, your computer-controlled agents will get smarter!

• Grail for scientists

  Depending on your research, you may:

  1. Extend Grail’s algorithms to introduce your new variants or test new hypotheses
     
  2. Use Grail as a multi-agent testing framework
     

  Grail provides high-quality implementations of Monte Carlo Tree Search (MCTS), Utility AI, Goal-Oriented Action Planner (GOAP) and Evolutionary Algorithm (EA). In addition, it includes basic implementation of Decision Trees that can be constructed automatically.

  A lot of research is based on or includes, in some form, one of these techniques. Although Grail has reasoners dedicated for game developers that encapsulate the algorithms, you can have access to their implementation as well. You can modify it, extend and carry out experiments aimed, for instance, at evaluating a particular MCTS extension, a hybrid approach or just an application of a particular technique in your research problem.

• Use Grail as a multi-agent testing framework

  In this case, examples of research include human-machine interaction, an analysis of how people play games and interact with computer-controlled characters, an analysis of emergent behavior, planning in a simulated environment, robotics, research in video games (in general), etc.

  Often, such research requires a simulated environment, in which there are agents controlled by the AI. Grail enables faster creation of such an environment by providing tools for defining agents’ behaviors.

• If Grail seems interesting to you, but you are not yet convinced, you may always try out our GUI Tool. It allows you to create AI system configurations and to define Utility AI presets using an intuitive graphical interface. Being a part of our Grail set, the GUI Tool allows you to experience first hand what working with Grail would be like. This tool aims to significantly decrease the time needed for AI debugging and frees you up, so you can do more interesting stuff (like adding new functionalities to your agents).

  Grail GUI Tools

Do you have any questions or need support?
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