Learning Game AI Programming with Lua PDF
Preview Learning Game AI Programming with Lua
Table of Contents Learning Game AI Programming with Lua Credits About the Author About the Reviewers www.PacktPub.com Support files, eBooks, discount offers, and more Why subscribe? Free access for Packt account holders Preface What this book covers What you need for this book Who this book is for Conventions Reader feedback Customer support Downloading the example code Downloading the color images of this book Errata Piracy Questions 1. Getting Started with AI Sandbox Introduction to AI sandbox Understanding the sandbox The project layout The Premake build Compiling the sandbox with Visual Studio 2008/2010/2012/2013 Open source libraries Open source tools Lua IDE – Decoda Running AI sandbox inside Decoda Setting up a new Decoda project Debugging Lua scripts Decoda Watch window Decoda Call Stack window The Decoda Virtual Machines window Simultaneous Lua and C++ debugging Visual Studio – Attach to Process Decoda – Attach to Process Decoda – Attach System Debugger Associating Lua scripts from code with Decoda The Lua virtual machine The Lua stack Lua primitives Metatables Metamethods Userdata C/C++ calling Lua functions Lua calling C/C++ functions Function binding Creating custom userdata Looking at the vector data type The demo framework Ogre Object-Oriented Input System SandboxApplication Sandbox Agent Utility classes Lua binding Summary 2. Creating and Moving Agents Creating a new sandbox project Setting up the file structure Extending the SandboxApplication class Running your sandbox for the first time Creating a new Decoda project Configuring Decoda's run executable Creating a sandbox Lua script Creating a floor Adding a light Adding a skybox Adding meshes to the sandbox Creating sandbox objects Shooting blocks Creating an agent Lua script Creating a visual representation Updating an agent position Updating an agent orientation Agent properties Orientation The forward axis The left axis The up axis Location Position Size Height Radius Physics Mass The max force The max speed Speed Velocity Knowledge Target Target radius Path Agents' movement Mass Speed Velocity Acceleration Force Agent-steering forces Seeking Applying steering forces to an agent Clamping the horizontal speed of an agent Creating a seeking agent Pursuit Fleeing Evasion Wandering The target speed Path following Creating a path following agent Avoidance Collision avoidance Obstacle avoidance Avoiding blocks and agents Group steering Alignment Cohesion Separation Creating a group of followers Summing steering forces Weighted sums Priority-based forces Summary 3. Character Animations Skeletons and meshes Mesh skeletons Loading an animated mesh Showing a skeleton Attaching meshes to bones Attaching a weapon to our soldier Animation clips Playing an animation on our soldier Soldier animations Crouching animations Standing animations Weapon animations Soldier poses Weapon poses Manipulating animations Enabling and disabling animations Looping animations The animation length The animation time Normalized time Restarting an animation Playing a non-looping animation The animation rate Animation blending Animation weights Blend window Blend curves Linear blending Playing with blend weights Animation state machine (ASM) States Transitions Creating animation state machines Creating helper functions Adding states Adding transitions Adding external helper functions Forcefully setting states Requesting states Updating the animation state machine Handling state transitions and state requests Updating running animations Adding functions to animation state machine instances Building a weapon animation state machine Building a soldier animation state machine Updating animation state machines Playing with states Summary 4. Mind Body Control Creating a body Creating a soldier Attaching an animated mesh to an agent Creating an obstacle course Displaying the physics world Adding callbacks to the animation state machine Handling callbacks Adding callbacks to the ASM Updating the ASM to call callbacks Getting our soldier to shoot The bone position The bone rotation Creating particle effects The particle direction Object removal The collision impact callback Shooting a projectile Handling projectile collision impacts Shooting Getting our soldier to run Setting a path through the obstacle course Running the obstacle course Creating a brain Approaches for mind body control Direct animation control The death state The idle state The falling state The moving state The shooting state A simple, finite state machine Initializing the agent Agent FSM state handling Indirect animation control The animation controller Commands The command queue Manipulating commands The change stance command The die command The fall command The idle command The move command The shoot command Assigning member functions Initializing the controller Adding handlers for commands Updating the controller Running the obstacle course Creating a direct control agent Creating an indirect control agent Indirect control agent initialization Indirect control agent update Indirect control agent control Spawning an indirect control agent Action latency Summary 5. Navigation Pathfinding Creating a navigation mesh Configuring navigation meshes The walkable height The walkable radius The walkable climb height The walkable slope angle The minimum region area Building the navigation mesh Drawing the navigation mesh Pathfinding on a navigation mesh Path query Query results Random navigation points The path information Adding random pathfinding to our soldier Updating agent paths Drawing paths Initializing the navmesh Randomly running agents Creating additional navigation meshes Summary 6. Decision Making Creating userdata Agent actions Adding data members Initializing an action Updating an action Action cleanup Action member functions Creating actions The idle action The die action The reload action The shoot action The random move action The move action The flee action The pursue action Evaluators Creating evaluators Constant evaluators Has ammo evaluator Has critical health evaluator Has enemy evaluator Has move position evaluator Is alive evaluator Can shoot enemy evaluator 50/50 chance evaluator Decision structures Decision trees Branches Decision leaves Branch evaluation Building a decision tree Creating branches Creating a decision tree agent Strengths of decision trees Pitfalls of decision trees Finite state machines States Transitions Finite state machine structure Helper functions Adding states and transitions Updating the finite state machine Adding instance functions Building a finite state machine The idle state The movement state The random movement state The shoot state The flee state The die state The pursue state The reload state Creating a finite state machine agent Strengths of finite state machines Pitfalls of finite state machines Behavior trees The behavior tree node Helper functions Updating the behavior tree node Actions Conditions Selectors Sequences Creating a behavior tree object Behavior tree helper functions Selector evaluation Sequence evaluation Node evaluation Continue behavior tree evaluation The behavior tree update loop Updating the behavior tree Building a behavior tree The death behavior The flee behavior Combat behaviors The reload behavior The shoot behavior The pursue behavior The move behavior The random move behavior The idle behavior Creating a behavior tree agent Strengths of behavior trees Pitfalls of behavior trees Summary 7. Knowledge Representation Knowledge sources Creating a knowledge source Knowledge source evaluation Blackboards Creating a blackboard Adding and removing knowledge sources Evaluating knowledge sources Setting and retrieving blackboard attributes Blackboard member functions Creating soldier knowledge sources Enemy selection Flee position selection Constructing a soldier blackboard Updating decision evaluators Updating behavior actions The die action The flee action The idle action The move action The pursue action The reload action The shoot action Summary 8. Perception Events Attributes Sending events Receiving events Managing events Assigning agent teams Handling agent communications Event types Creating agent senses Initializing senses Updating senses Agent visibility Detecting other visible agents Agent sighting events New enemy sighted event New dead enemy body sighted event New dead teammate body sighted event Handling new agent sightings Intermittent agent sightings Throttling agent visibility updates Creating event handlers Adding event handlers Agent auditory senses Auditory events The BulletShot event The BulletImpact event Handling auditory events Decaying blackboard events Decaying auditory events Team communications The EnemySelection event The PositionUpdate event The RetreatPosition event Updating agent behaviors Enemy selection Scoring dangerous positions Score danger from bullet impacts Score danger from bullet shots Score danger from enemies Score danger from dead bodies Calculating the best flee position Summary 9. Tactics Influence maps The cell height The cell width Constructing an influence map Configuration Voxelizing a navigation mesh Drawing influence maps Accessing influences Setting influences Getting influences Clearing influences Spreading influences Cell inertia Cell falloff Influence map layers Updating the influence map Soldier tactics Initializing and updating tactics Scoring team influences Initializing team influences Updating team influences
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