bevy_rl
Build Reinforcement Learning Gym environments
with Bevy engine to train AI agents that learn from raw screen pixels.
Compatibility
| bevy version |
bevy_rl version |
| 0.7 |
0.0.5 |
| 0.8 |
0.8.4 |
Features
- Set of APIs to implement OpenAI Gym interface
- REST API to control an agent
- Rendering to RAM membuffer
Changelog
- 0.8.4
- Added object representation of observation space
Usage
1. Define App States
#[derive(Debug, Clone, Eq, PartialEq, Hash)]
enum AppState {
InGame, Control, Reset, }
### 2. Define Action Space and Observation Space
A action space is a set of actions that an agent can take. An observation space is a set of observations that an agent can see. Action space can be discrete or continuous. Observations should be serializable to JSON with `serde_json` crate.
```rust
bitflags! {
#[derive(Default)]
pub struct PlayerActionFlags: u32 {
const FORWARD = 1 << 0;
const BACKWARD = 1 << 1;
const LEFT = 1 << 2;
const RIGHT = 1 << 3;
}
}
#[derive(Default, Serialize, Clone)]
pub struct EnvironmentState {
pub map: GameMap,
pub actors: Vec<Actor>,
}
3. Enable AI Gym Plugin
Width and hight should exceed 256, otherwise wgpu will panic.
let gym_settings = AIGymSettings {
width: 256,
height: 256,
num_agents: 16,
};
app
.insert_resource(gym_settings.clone())
.insert_resource(Arc::new(Mutex::new(AIGymState::<
PlayerActionFlags,
EnvironmentState,
>::new(gym_settings.clone()))))
.add_plugin(AIGymPlugin::<PlayerActionFlags, EnvironmentState>::default())
4. Implement environment logic
DelayedControlTimer should pause environment execution to allow agents to take actions.
struct DelayedControlTimer(Timer);
Define systems that implement environment logic.
app.add_system_set(
SystemSet::on_update(AppState::InGame)
.with_system(turnbased_control_system_switch),
);
app.insert_resource(DelayedControlTimer(Timer::from_seconds(0.1, true))); app.add_system_set(
SystemSet::on_update(AppState::Control)
.with_system(turnbased_text_control_system) .with_system(execute_reset_request), );
turnbased_control_system_switch should pause game world and poll bevy_rl for agent actions.
fn turnbased_control_system_switch(
mut app_state: ResMut<State<AppState>>,
time: Res<Time>,
mut timer: ResMut<DelayedControlTimer>,
ai_gym_state: ResMut<Arc<Mutex<AIGymState<PlayerActionFlags>>>>,
) {
if timer.0.tick(time.delta()).just_finished() {
app_state.push(AppState::Control);
physics_time.pause();
let ai_gym_state = ai_gym_state.lock().unwrap();
ai_gym_state.send_step_result(true);
}
}
execute_reset_request handles environment reset request. turnbased_control_system_switch in this example parses agent actions and issues commands to agents in environment via control_agents.
pub(crate) fn execute_reset_request(
mut app_state: ResMut<State<AppState>>,
ai_gym_state: ResMut<Arc<Mutex<AIGymState<PlayerActionFlags>>>>,
) {
let ai_gym_state = ai_gym_state.lock().unwrap();
if !ai_gym_state.is_reset_request() {
return;
}
ai_gym_state.receive_reset_request();
app_state.set(AppState::Reset).unwrap();
}
pub(crate) fn turnbased_control_system_switch(
mut app_state: ResMut<State<AppState>>,
time: Res<Time>,
mut timer: ResMut<DelayedControlTimer>,
ai_gym_state: ResMut<Arc<Mutex<AIGymState<PlayerActionFlags>>>>,
ai_gym_settings: Res<AIGymSettings>,
mut physics_time: ResMut<PhysicsTime>,
) {
if timer.0.tick(time.delta()).just_finished() {
app_state.overwrite_push(AppState::Control).unwrap();
physics_time.pause();
let ai_gym_state = ai_gym_state.lock().unwrap();
let results = (0..ai_gym_settings.num_agents).map(|_| true).collect();
ai_gym_state.send_step_result(results);
}
}
pub(crate) fn turnbased_text_control_system(
agent_movement_q: Query<(&mut heron::prelude::Velocity, &mut Transform, &Actor)>,
collision_events: EventReader<CollisionEvent>,
event_gun_shot: EventWriter<EventGunShot>,
ai_gym_state: ResMut<Arc<Mutex<AIGymState<PlayerActionFlags>>>>,
ai_gym_settings: Res<AIGymSettings>,
mut app_state: ResMut<State<AppState>>,
mut physics_time: ResMut<PhysicsTime>,
) {
let mut ai_gym_state = ai_gym_state.lock().unwrap();
if !ai_gym_state.is_next_action() {
return;
}
let unparsed_actions = ai_gym_state.receive_action_strings();
let mut actions: Vec<Option<PlayerActionFlags>> =
(0..ai_gym_settings.num_agents).map(|_| None).collect();
for i in 0..unparsed_actions.len() {
let unparsed_action = unparsed_actions[i].clone();
ai_gym_state.set_reward(i, 0.0);
if unparsed_action.is_none() {
actions[i] = None;
continue;
}
let action = match unparsed_action.unwrap().as_str() {
"FORWARD" => Some(PlayerActionFlags::FORWARD),
"BACKWARD" => Some(PlayerActionFlags::BACKWARD),
"LEFT" => Some(PlayerActionFlags::LEFT),
"RIGHT" => Some(PlayerActionFlags::RIGHT),
_ => None,
};
actions[i] = action;
}
ai_gym_state.set_env_state(EnvironmentState {});
physics_time.resume();
control_agents(actions, agent_movement_q, collision_events, event_gun_shot);
app_state.pop().unwrap();
}
AIGymState API
| Method |
Description |
send_step_result(results: Vec<bool>) |
Send upon agents interactions are complete |
send_reset_result(result: bool) |
Send when reset request is complete |
receive_action_strings(Vec<Option<String>>) |
Recieve environment for agent actions |
receive_reset_request() |
Recieve environment for reset request |
is_next_action() -> bool |
Whether agent actions are supplied |
is_reset_request() -> bool |
Whether reset request was sent |
set_reward(agent_index: usize, score: f32) |
Set reward for an agent |
set_terminated(agent_index: usize, result: bool) |
Set termination status for an agent |
reset() |
Reset bevy_rl state |
set_env_state(state: B) |
Set current environment state |
REST API
| Method |
Verb |
bevy_rl version |
| Camera Pixels |
GET |
http://localhost:7878/visual_observations |
| State |
GET |
http://localhost:7878/state |
| Reset Environment |
POST |
http://localhost:7878/reset |
| Step |
GET |
http://localhost:7878/step payload=ACTION |
Examples
bevy_rl_shooter — example FPS project