Inspector-based GOAP AI system with A* planning, sensors, async planning,
and a visual graph editor. No hand-crafted state machines needed.GOAP Engine lets your AI agents automatically plan and execute sequencesof actions to reach their goals — without hand-crafting state machines orbehaviour trees. The planner uses A* search to find the cheapest validaction chain from the current world state to the desired goal state.HOW IT WORKSConfigure goals, actions, requirements, and effects entirely from theInspector. The planner handles everything — finding the optimal actionsequence at runtime, re-planning reactively when the world changes, andlocking resources to prevent conflicts between multiple agents.PLANNING SYSTEMA* search with admissible heuristic (guaranteed optimal plans)Async (threaded) planning — A* runs on a background threadGC-optimized — flat float[] state arrays, node pool, state poolPlan cache — repeated state+goal combos skip the search entirelyRelevance-based re-planning — only re-plans when relevant state changesReactive re-planning triggered by state change events (no polling)INSPECTOR-BASED SETUPGoals, actions, requirements, and effects — all configured in InspectorNo code required for basic AI setupsAction Creator window generates boilerplate-free action subclassesBehaviorPreset ScriptableObject for shareable behavior configurationsSENSOR SYSTEMRangeSensor — sphere-based detection with Physics.OverlapSphereLineOfSightSensor — FOV cone + raycast obstruction checkConfigurable poll interval, output modes (Boolean/Count/NearestDistance)Writes directly into behavior state — triggers reactive re-planningMULTI-TARGET NAVIGATIONTargetBinder component — attach to any scene objectAutomatic resource locking — prevents two agents claiming the same targetShared targets — allow multiple agents simultaneously (waypoints, etc.)Dynamic costs — distance-based or context-based cost per planning cycleTarget wait timeout — hold plan and retry before switching goalsFEATURESDSL Expressions — compact string syntax for requirements and effectsConditional Effects — And/Or condition guards on individual effectsParametric Actions — one class, multiple Inspector-configured variantsPlan Ordering — enforce action order with name DSL ([After]/[Before])Goal Evaluator — custom A* scoring function for urgency/distance biasIncludeOnPlanning flag — disable actions without removing from InspectorSHOOTER ENEMY ACTIONSEight ready-to-use action classes: PatrolAction · ChaseAction ·FireWeaponAction · TakeCoverAction · ReloadAction · AlertAction ·InvestigateAction · PickUpActionCHARACTER SYSTEM (Optional)Includes Character component and plug-in abilities:Movement · Run · Jump · Rotate · Input · Weapon · PickUp · Health ·Animation · IK · HUD · NavMesh · CameraGOAP GRAPH EDITORVisual node graph of the full action/goal/state dependency network.Design-time: full dependency view, Inspector panel, Edit Script buttonPlay-mode: live state values, running action highlight, runtime overlayUndo/redo node moves, subclass field supportVersion: 1.3Unity Version: 2022.3 LTS and newer (C# 9 pattern matching required)Render Pipeline: Built-in, URP, HDRP (no render pipeline dependency)C# Language Version: C# 9.0+Scripting Backend: Mono and IL2CPP supportedTarget Platforms: All Unity-supported platformsDependencies (Required):Unity AI Navigation package (NavMeshAgent)Dependencies (Optional):GOAPENGINE_CHARACTER scripting define — activates Character SystemNo other third-party packages requiredPlanning System:Algorithm: A* search with flat float[] state arraysThreading: BeginPlan() on main thread; StepPlanAsync() on ThreadPoolGC: node pool, state pool, pre-allocated merged state dictionaryPlan cache: up to 16 plans cached by (startStateHash, goalHash)Package Contents:Runtime/ — AIBehavior, AIAgent, Planner, Actions, Sensors, TargetBinder, WorldStates, BehaviorPreset, Character SystemEditor/ — GOAP Graph Editor, Action Creator, custom inspectorsDemo/ — Premade shooter enemy actions and demo sceneSupport: beelabs446@gmail.comDocumentation: https://beelabs-dev.gitbook.io/beelabs-docs
