rgoap

A simplistic Rust implementation of Orkin's Goal-Oriented Action-Planner (GOAP), as described on his website.

Find the crate documentation on docs.rs, or here on Github.

This implementation is simplistic, as it doesn't handle many features, such as procedural pre- and post-conditions, dynamic action cost, non-binary world state, etc. But it is very short (thanks to the pathfinding crate by Samuel Tardieu). It has been written as a project to learn more about Rust - use with caution.

Usage

Add the rgoap dependency to Cargo.toml:

[dependencies]
rgoap = "0.1"

And use the crate as such:

extern crate rgoap;

use rgoap::{State, Action, plan};

fn main() {
    // The actions your planner will be allowed to use.
    let mut walk_to_dog = Action::new("walk_to_dog".to_string(), 1);
    walk_to_dog.pre_conditions.insert("dog_person".to_string(), true);
    walk_to_dog.post_conditions.insert("near_dog".to_string(), true);

    let mut dog_wiggles_tail = Action::new("dog_wiggles_tail".to_string(), 1);
    dog_wiggles_tail.pre_conditions.insert("dog_happy".to_string(), true);
    dog_wiggles_tail.post_conditions.insert("tails_wiggling".to_string(), true);

    let mut pet_dog = Action::new("pet_dog".to_string(), 1);
    pet_dog.pre_conditions.insert("near_dog".to_string(), true);
    pet_dog.post_conditions.insert("dog_happy".to_string(), true);

    let possible_actions = [walk_to_dog, pet_dog, dog_wiggles_tail];

    // This is the initial state of the world.
    let mut initial_state = State::new();
    initial_state.insert("near_dog".to_string(), false);
    initial_state.insert("dog_person".to_string(), true);
    initial_state.insert("dog_happy".to_string(), false);
    initial_state.insert("tails_wiggling".to_string(), false);

    // And this is the target state. Note that it doesn't have to include all of the states.
    let mut goal_state = State::new();
    goal_state.insert("tails_wiggling".to_string(), true);

    // Let's find which actions needs to happen to get there.
    let planned_actions = plan(&initial_state, &goal_state, &possible_actions).unwrap();

    // Are the actions what we expected?
    let planned_actions_names: Vec<String> =
        planned_actions.iter().map(|&action| action.name.clone()).collect();
    let expected_actions_names =
        vec!["walk_to_dog".to_string(), "pet_dog".to_string(), "dog_wiggles_tail".to_string()];

    assert_eq!(planned_actions_names, expected_actions_names);
}

License

MIT - See LICENSE file.