# luxkun/ReGoap

Generic C# GOAP (Goal Oriented Action Planning) library with Unity3d examples

Repository: https://github.com/luxkun/ReGoap
Canonical: https://ross.abutalabs.com/products/regoap
Language: C#
License: Apache-2.0
License Family: permissive
Topics: unity, goap, ai, gamedev
Last push: 2026-04-21T19:42:00+00:00

## Health v2 (maintenance only)
Score: 58/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 78, release rhythm 8, longevity 100
- inputs: {"age_days": 3575, "days_push": 134, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1111, forks 155 (observed 2026-08-28T04:03:37.720281+00:00)

## What it is
ReGoap is a generic C# GOAP (Goal Oriented Action Planning) library with adapters for Unity and Godot. It provides an engine-agnostic planner core that uses A* search to build action sequences for agents based on goals, actions, memory, and sensors.

## Use cases
- implement NPC AI with goal-oriented action planning in Unity
- create emergent enemy behavior without hardcoded state machines
- build simulation agents that replan when world state changes
- define agent goals and actions with preconditions and effects in C#
- use GOAP planning in Godot games
- model inventory and resource-driven NPC decisions like crafting or gathering

## When to choose
- you want flexible, emergent NPC behavior instead of behavior trees or switch-based AI
- you need a reusable, engine-agnostic GOAP core with Unity or Godot integration
- your agents must replan dynamically in response to world changes
- you need comparator-based conditions for counts, thresholds, and inventory logic

## When to avoid
- you need simple scripted enemy behavior that a state machine handles fine
- you want a visual behavior tree editor or node-based AI authoring
- your project is not in C# or does not use Unity/Godot
- you need machine-learning-driven agents rather than symbolic planning

## Facets
- artifact type: library
- maturity: active
- function: game-engine, simulation, machine-learning
- domain: artificial-intelligence, simulation
- platform: cross-platform, game-engine
- tags: goap, goal-oriented-action-planning, npc-ai, unity, godot, csharp, gamedev, a-star-planning, game-development

## Member repositories
- luxkun/ReGoap (main) score 58

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:37.720281+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:43:24.494553+00:00, confidence not recorded.
  - readme: https://github.com/luxkun/ReGoap (fetched 2026-08-28T04:03:37.720281+00:00, sha 4da194dc2690)
- Data as of 2026-08-30T08:39:29.467469+00:00.