舉報 
會員
Unity Artificial Intelligence Programming
DevelopingArtificialIntelligence(AI)forgamecharactersinUnity2018hasneverbeeneasier.UnityprovidesgameandappdeveloperswithavarietyoftoolstoimplementAI,fromthebasictechniquestocutting-edgemachinelearning-poweredagents.LeveragingthesetoolsviaUnity'sAPIorbuilt-infeaturesallowslimitlesspossibilitieswhenitcomestocreatingyourgame'sworldsandcharacters.ThisfourtheditionwithUnitywillhelpyoubreakdownAIintosimpleconceptstogiveyouafundamentalunderstandingofthetopictobuildupon.Usingavarietyofexamples,thebookthentakesthoseconceptsandwalksyouthroughactualimplementationsdesignedtohighlightkeyconceptsandfeaturesrelatedtogameAIinUnity.Furtheron,you'lllearnhowtodistinguishthestatemachinepatternandimplementoneofyourown.ThisisfollowedbylearninghowtoimplementabasicsensorysystemforyourAIagentandcouplingitwithaFiniteStateMachine(FSM).Next,you'lllearnhowtouseUnity'sbuilt-inNavMeshfeatureandimplementyourownA*pathfindingsystem.You'llthenlearnhowtoimplementsimple?ocksandcrowddynamics,whicharekeyAIconceptsinUnity.Movingon,you'lllearnhowtoimplementabehaviortreethroughagame-focusedexample.Lastly,you'llapplyalltheconceptsinthebooktobuildapopulargame.
目錄(160章)
倒序
- coverpage
- Title Page
- Dedication
- About Packt
- Why subscribe?
- Packt.com
- Contributors
- About the authors
- About the reviewer
- Packt is searching for authors like you
- Preface
- Who this book is for
- What this book covers
- To get the most out of this book
- Download the example code files
- Download the color images
- Conventions used
- Get in touch
- Reviews
- Introduction to AI
- Artificial Intelligence (AI)
- AI in games
- AI techniques
- Finite State Machines (FSMs)
- Random and probability in AI
- The sensor system
- Polling
- The messaging system
- Flocking swarming and herding
- Path following and steering
- A* pathfinding
- A navigation mesh
- The behavior trees
- Locomotion
- Summary
- Finite State Machines
- The player's tank
- Initialization
- Shooting bullet
- Controlling the tank
- The Bullet class
- Setting up waypoints
- The abstract FSM class
- The enemy tank AI
- The Patrol state
- The Chase state
- The Attack state
- The Dead state
- Taking damage
- Using an FSM framework
- The AdvanceFSM class
- The FSMState class
- The state classes
- The PatrolState class
- The NPCTankController class
- Summary
- Randomness and Probability
- Randomness in games
- Randomness in computer science
- The Unity Random class
- Simple random dice game
- Definitions of probability
- Independent and related events
- Conditional probability
- Loaded dice
- Character personalities
- FSM with probability
- Dynamic AI
- Demo slot machine
- Random slot machine
- Weighted probability
- Near miss
- Summary
- Further reading
- Implementing Sensors
- Basic sensory systems
- Scene setup
- The player's tank and the aspect class
- The player's tank
- Aspect
- AI characters
- Sense
- Sight
- Touch
- Testing
- Summary
- Flocking
- Basic flocking behavior
- Individual behavior
- Controller
- Alternative implementation
- FlockController
- Summary
- Path-Following and Steering Behaviors
- Following a path
- Path script
- Path-following agents
- Avoiding obstacles
- Adding a custom layer
- Obstacle avoidance
- Summary
- A* Pathfinding
- Revisiting the A* algorithm
- Implementing the A* algorithm
- Node
- PriorityQueue
- The GridManager class
- The AStar class
- The TestCode class
- Setting up the scene
- Testing the pathfinder
- Summary
- Navigation Mesh
- Setting up the map
- Navigation static
- Baking the navigation mesh
- NavMesh agent
- Updating an agents' destinations
- The Target.cs class
- Scene with slope
- Navigation areas
- Off Mesh Links
- Generated Off Mesh Links
- Manual Off Mesh Links
- Summary
- Behavior Trees
- Introduction to Behavior Trees
- A simple example – patrolling robot
- Implementing a BT in Unity with Behavior Bricks
- Set up the scene
- Implement a Day/Night cycle
- Design the Enemy Behavior
- Implement the Nodes
- Building the Tree
- Attach the BT to the Enemy
- Summary
- External Resources
- Machine Learning in Unity
- The Unity Machine Learning Agents Toolkit
- How to install the ML-Agents Toolkit
- Installing Python and TensorFlow on Windows
- Installing Python and TensorFlow on macOS and Unix-like systems
- Using the ML-Agents Toolkit – a basic example
- Creating the scene
- Implementing the code
- Adding the final touches
- Training a Brain object
- Training the agent
- Summary
- Further reading
- Putting It All Together
- Basic game structure
- Adding automated navigation
- Creating the NavMesh
- Setting up the agent
- Fixing the GameManager script
- Creating decision-making AI with FSM
- Summary
- Other Books You May Enjoy
- Leave a review - let other readers know what you think 更新時間：2021-06-10 18:58:16
推薦閱讀
- Mastering Machine Learning for Penetration Testing
- 物聯網安全（原書第2版）
- Building E-commerce Sites with VirtueMart Cookbook
- Proxmox High Availability
- 新一代物聯網架構技術：分層算力網絡
- 計算機網絡安全實訓教程（第二版）
- 智慧城市中的移動互聯網技術
- PLC、現場總線及工業網絡實用技術速成
- Wireshark網絡分析就這么簡單
- The Kubernetes Workshop
- 面向5G-Advanced的關鍵技術
- Learning Node.js Development
- 深入理解計算機網絡
- Hands-On Docker for Microservices with Python
- 圖解物聯網
- 移動互聯網環境下的核心網剖析及演進
- Hands-On Reactive Programming in Spring 5
- 趣話通信：6G的前世、今生和未來
- Learn Node.js by Building 6 Projects.
- 網絡是怎樣連接的
- 物聯網工程應用技術
- 5G時代：生活方式和商業模式的大變革
- 計算機聯鎖及信號微機監測系統
- 網絡故障現場處理實踐（第2版）
- Node-RED物聯網應用開發工程實踐
- Exchange Server 2013 SP1管理實踐
- Vue.js 2 Design Patterns and Best Practices
- Asterisk權威指南（原書第5版）
- 崛起的超級智能：互聯網大腦如何影響科技未來
- 物聯網服務平臺技術
