面向目标的行动计划（GOAP）是一种AI架构，可为游戏角色提供选择目标的能力，并根据环境状况和可用资源制定计划以实现这些目标。它可以用于从第一人称射击游戏到实时策略的各种游戏类型，以开发能够做出明智决策的智能角色，而无需大型有限状态机。该代码库看似简单，但又逻辑合理，可重用且功能强大。该库是用C＃编写的，并在Unity V.2019中实现，但是可以轻松移植到其他应用程序。
在本课程中，Penny凭借其享誉国际的教学风格和25多年的游戏，图形学知识以及撰写了两本屡获殊荣的游戏AI书籍，揭晓了GOAP先进的AI技术，该技术用于在游戏中创建真实可信的游戏角色。在整个过程中，您将跟随动手研讨会，这些研讨会将带您完成将自己的GOAP API组合在一起的每个步骤。您将从头开始构建整个GOAP库，同时并行构建医院模拟方案，以在进行过程中测试API。
内容和概述
在整个课程中，您将从头开始构建GOAP库和API，以使您对代码库有深入的了解。除此之外，还将构建一个简单的医院模拟程序，以测试图书馆放在一起时的功能。模拟还将依赖Unity的NavMesh系统进行导航和路径规划。
该课程首先概述了Unity的NavMesh系统，并涵盖了医院模拟所需的基本功能。然后，它涵盖了GOAP的概念，在该概念中，学生将发现目标，行动和计划是如何相互作用的。将构建一个计划程序，该计划程序将根据每个角色在模拟中所认为的目标来动态构建每个角色的动作序列。
此后，将引入和开发清单以容纳各个角色的资源。库存中的资源将用于计划的完成，还有助于指导角色在环境中的导航。然后，这将建立更复杂的行为的设计，其中两个角色必须协作才能完成计划。
随着课程的继续，将添加更多角色不同的角色并进行动态创建，并添加和删除资源以开发复杂的模拟。在课程结束时，学生将在医院中模拟病人，护士，医生和看门人，每个人都有各自的角色，目标，行动和所需的资源。
尽管本课程的目的不是构建完整的游戏，但最后一部分将提供有关Unity开发的更多知识，并研究与环境进行交互的方法，例如：拖放项目，动态NavMesh烘焙，用户界面创建和摄像头移动以提供对如何将这种模拟转化为游戏有一定指导的学生。
完成本课程后，学生将拥有完整的GOAP库和API，他们可以在自己的游戏项目中重用它们，以提供具有复杂智能行为的游戏角色。
Highest Rated | h264, yuv420p, 1280×720 |ENGLISH, aac, 44100 Hz, 2 channels | 8h 07 mn | 5.14 GB
Instructor: Penny de Byl, Penny
Artificial Intelligence for Creating Complex Game Character Behaviours for Simulations, Real-Time Strategy Games & More
What you’ll learn
How to design and program more intelligent behaving Non-Player Characters with C#.
How goals, states, actions, believes and path-planning can be applied in computer games.
The finer workings of a Goal-Oriented Action Planning (GOAP) library and building one from scratch.
How to develop and debug your own simulations.
Requirements
You should be familiar with C# and the Unity Game Development Engine.
Description
Goal-Oriented Action Planning (GOAP) is an AI architecture that provides game characters with the ability to select goals and make plans to achieve those goals based on the state of the environment and available resources. It can be used across a wide range of game genres from first-person shooters to real-time strategies, to develop intelligent characters capable of making smart decisions without the need for large finite state machines. The codebase is deceptively simple and yet logical, reusable and extremely powerful. The library is written in C# and implemented in Unity V.2019, however will easily port to other applications.
In this course, Penny demystifies the advanced AI technique of GOAP used for creating believable and intelligent game characters in games using her internationally acclaimed teaching style and knowledge from over 25 years working with games, graphics and having written two award-winning books on games AI. Throughout, you will follow along with hands-on workshops designed to take you through every step of putting together your own GOAP API. You will build the entire GOAP library from the ground up while building a hospital simulation scenario in parallel, to test the API as you go.
Learn how to program and work with:
A GOAP Library and API that’s reusable across a wide range of game projects.
Goals, Actions, States and Beliefs that define the state of the game environment, what individual characters want to do and how they understand their world.
Navigation Meshes and Agents that provide advanced path planning and navigation capabilities for characters.
Dynamic Building of NavMeshes to allow for the repositioning of resources in the environment.
Inventories for each character for use in completing tasks that satisfy character goals.
The Unity UI system to move draggable resources into a game environment.
Contents and Overview
Throughout the course, you will follow along while a GOAP library and API are constructed from the ground up, to allow you intimate knowledge of the codebase. Alongside this, a simple hospital simulation will be constructed to test out the functionality of the library as it is put together. The simulation will also rely on Unity’s NavMesh System for navigation and path planning.
The course begins with an overview of Unity’s NavMesh System and covers the basic functionality needed for the hospital simulation. It then goes on to cover the concept of GOAP, where students will discover how goals, actions and plans interact. A planner will be constructed that dynamically builds each character’s sequence of actions, based on what they believe their goals are while in the simulation.
Following this, inventories will be introduced and developed to hold resources for individual characters. The resources in the inventories will be required for plan completion and also assist in directing a character’s navigation around the environment. This will then build to the design of more complex behaviours in which two characters must collaborate to complete a plan.
As the course continues, more characters with differing roles will be added and dynamically created and resources will be added and removed to develop a complex simulation. By the end of the course, students will have a hospital simulation with patients, nurses, doctors and janitors each with their own roles, goals, actions and required resources.
Although this course is not about building a completed game, a final section will provide some further knowledge on Unity development and examine methods for interacting with the environment such as: dragging and dropping items, dynamic NavMesh baking, user interface creation and camera movement to provide students with some direction on how such a simulation could be turned into a game.
At the completion of this course, students will have a fully-fledged GOAP library and API that they can reuse in their own game projects to provide game characters with complex intelligent behaviours.
What students are saying about Penny’s courses:
Turns out, the hardest part of this course for me is finding the words to describe how glad I am to have enrolled in it.
I honestly love Hollistic’s teaching approach and I’ve never learned so much within a few hours about coding effectively with such detailed explanations!
Penny is an excellent instructor and she does a great job of breaking down complex concepts into smaller, easy-to-understand topics.
Who this course is for:
Anyone interested in learning how to better program their own non-player characters (NPCs) for believable behaviour.
Anyone wanting to learn the advanced AI technique of GOAP to control their sims.
Anyone interested in seeing how artificial intelligence is applied in computer games.
原创文章，作者：steven，如若转载，请注明出处：https://rr3d.cn/11370.html
