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Unlike behavior trees or state machines, plans are computed at runtime based on current world state and available actions.\n\n**Key features:**\n- Automatic plan generation via backward-chaining search\n- Cost-based path selection\n- Dynamic state evaluation at runtime\n- Action hierarchies with preconditions and effects\n- Extensible via TypeScript mixins\n\n## Installation\n\n```bash\nnpm install @ankhzet/goap\n# or\nyarn add @ankhzet/goap\n# or\npnpm add @ankhzet/goap\n```\n\nRequires TypeScript 4.0+ or ES2018+ runtime.\n\n## Quick Start\n\n```typescript\nimport {\n Action,\n ActionEnactor,\n ActionProcessingResult,\n EnactorState,\n GoalActionPlanner,\n GoalActionExecutor,\n StateBitInterface,\n StateInterface\n} from 'goap';\n\n// Define state bits\nconst isHungry: StateBitInterface = { name: 'isHungry' };\nconst hasFood: StateBitInterface = { name: 'hasFood' };\n\n// Define actions\nclass EatAction extends Action {\n cost = 1;\n requires = new EnactorState([[isHungry, true]]);\n provides = new EnactorState([[hasFood, true]]);\n\n process(enactor: Agent): ActionProcessingResult {\n enactor.hunger = 100;\n return ActionProcessingResult.Finished;\n }\n}\n\n// Create agent\nclass Agent extends ActionEnactor(BaseClass) {\n actions = new Set([new EatAction()]);\n state = new EnactorState();\n deriveGoal(): StateInterface {\n return new EnactorState([[hasFood, true]]);\n }\n}\n\n// Plan and execute\nconst planner = new GoalActionPlanner();\nconst executor = new GoalActionExecutor();\n\nconst plan = planner.plan(agent, agent.deriveGoal(), agent.state);\nif (plan) {\n agent.acceptSequence(plan);\n // In game loop:\n executor.process(agent, delta);\n}\n```\n\n## Documentation\n\n- [Core Concepts](./docs/core-concepts.md) - State system, actions, goals, planner algorithm\n- [Public API](./docs/public-api.md) - Complete type and method reference\n- [Examples](./docs/) - Real-world usage patterns\n\n### Examples\n\n| Domain | Description |\n|--------|-------------|\n| [Game NPC AI](./docs/example-game-npc.md) | Survival game with hunger, health, combat, socialization |\n| [Warehouse Robot](./docs/example-warehouse-robot.md) | Pick-and-deliver logistics with battery management |\n| [Smart Home](./docs/example-smart-home.md) | Home automation with HVAC, lighting, security |\n| [Autonomous Vehicle](./docs/example-autonomous-vehicle.md) | Navigation with routing, obstacle avoidance, parking |\n\n## Core Concepts\n\n### State\n\nWorld state is represented as a collection of bits with boolean values:\n\n```typescript\nconst state = new EnactorState([\n [hasWeapon, true],\n [isHealthy, false]\n]);\n```\n\nState bits can be static or dynamic:\n\n```typescript\nconst nearEnemy = {\n name: 'nearEnemy',\n isFulfilledBy: (agent) => agent.distanceToEnemy < 10\n};\n```\n\n### Actions\n\nActions have preconditions (`requires`), effects (`provides`), and cost:\n\n```typescript\nclass MyAction extends Action {\n cost = 5;\n requires = new EnactorState([[hasAmmo, true]]);\n provides = new EnactorState([[enemyDead, true]]);\n\n process(enactor: Agent, delta: number): ActionProcessingResult {\n // Execution logic\n return ActionProcessingResult.Finished;\n }\n}\n```\n\n### Agents\n\nAgents combine state with available actions:\n\n```typescript\nclass MyAgent extends ActionEnactor(BaseClass) {\n actions = new Set>();\n state = new EnactorState();\n\n deriveGoal(): StateInterface {\n // Compute goal based on current needs\n return new EnactorState([[hasFood, true]]);\n }\n}\n```\n\n### Planning\n\nThe planner finds the cheapest sequence to achieve a goal:\n\n```typescript\nconst planner = new GoalActionPlanner();\nconst plan = planner.plan(agent, goal, currentState);\n// Returns ActionInterface[] or undefined\n```\n\n### Execution\n\nThe executor runs the planned sequence:\n\n```typescript\nconst executor = new GoalActionExecutor();\n\n// In game loop:\nconst isActing = executor.process(agent, delta);\nif (!isActing) {\n // Replan\n}\n```\n\n## API Overview\n\n| Class | Purpose |\n|-------|---------|\n| `EnactorState` | Mutable world state |\n| `Action` | Base action class |\n| `ActionWithTarget` | Action requiring movement |\n| `ActionEnactor` | Mixin for action-performing agents |\n| `GoalActionPlanner` | Plan generation |\n| `GoalActionExecutor` | Plan execution |\n\nSee [Public API](./docs/public-api.md) for complete reference.\n\n## License\n\nMIT\n","readmeFilename":"README.md"}