GameReadyGoap 1.2.0

<img src="https://github.com/Joy-less/GameReadyGoap/blob/main/Assets/Icon.jpg?raw=true" width=256/>

Game Ready Goap

An easy-to-use implementation of GOAP (Goal-Oriented Action Planning) to control game characters in C#.

Features

• Simple and performant, made for game development
• Expressive with minimal boilerplate
• Get as close as possible to "best-effort" goals

Usage

First, create an agent with initial states, goals and actions:

GoapAgent Agent = new() {
    // These describe the current state of your agent (character).
    States = new() {
        ...
    },
    // These are the states your agent is trying to achieve.
    Goals = [
        ...
    ],
    // These are the ways your agent can change their states.
    Actions = [
        ...
    ],
};

Then, finding a plan is easy:

Agent.FindPlan(); // or Agent.FindPlan(Goal);

Example

A farmer is balancing tending to his crops with resting. He can farm to increase his crop health, which requires energy, or sleep to increase his energy.

GoapAgent Farmer = new() {
    States = new() {
        ["Energy"] = 100,
        ["CropHealth"] = 0,
    },
    Goals = [
        new GoapGoal("TendToCrops") {
            Objectives = [
                new GoapCondition() {
                    State = "CropHealth",
                    Comparison = GoapComparison.GreaterThanOrEqualTo,
                    Value = 100,
                    BestEffort = true,
                },
            ],
        },
    ],
    Actions = [
        new GoapAction("Farm") {
            Effects = [
                new GoapEffect() {
                    State = "CropHealth",
                    Operation = GoapOperation.IncreaseBy,
                    Value = 20,
                },
                new GoapEffect() {
                    State = "Energy",
                    Operation = GoapOperation.DecreaseBy,
                    Value = 30,
                },
            ],
            Requirements = [
                new GoapCondition() {
                    State = "Energy",
                    Comparison = GoapComparison.GreaterThanOrEqualTo,
                    Value = 30,
                },
            ],
        },
        new GoapAction("Sleep") {
            Effects = [
                new GoapEffect() {
                    State = "Energy",
                    Operation = GoapOperation.IncreaseBy,
                    Value = 5,
                },
            ],
        },
    ],
};
Farmer.FindPlan();

We get 15 actions which bring us to our goal:

Special Thanks

• F.E.A.R. for creating the GOAP algorithm.
• This Is Vini for explaining the GOAP algorithm.
• SimpleGOAP for guidance when implementing the action planner.