120 lines
3.2 KiB
GDScript
120 lines
3.2 KiB
GDScript
extends Node3D
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class_name AIController3D
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enum ControlModes { INHERIT_FROM_SYNC, HUMAN, TRAINING, ONNX_INFERENCE, RECORD_EXPERT_DEMOS }
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@export var control_mode: ControlModes = ControlModes.INHERIT_FROM_SYNC
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@export var onnx_model_path := ""
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@export var reset_after := 1000
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@export_group("Record expert demos mode options")
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## Path where the demos will be saved. The file can later be used for imitation learning.
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@export var expert_demo_save_path: String
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## The action that erases the last recorded episode from the currently recorded data.
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@export var remove_last_episode_key: InputEvent
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## Action will be repeated for n frames. Will introduce control lag if larger than 1.
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## Can be used to ensure that action_repeat on inference and training matches
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## the recorded demonstrations.
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@export var action_repeat: int = 1
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@export_group("Multi-policy mode options")
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## Allows you to set certain agents to use different policies.
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## Changing has no effect with default SB3 training. Works with Rllib example.
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## Tutorial: https://github.com/edbeeching/godot_rl_agents/blob/main/docs/TRAINING_MULTIPLE_POLICIES.md
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@export var policy_name: String = "shared_policy"
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var onnx_model: ONNXModel
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var heuristic := "human"
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var done := false
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var reward := 0.0
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var n_steps := 0
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var needs_reset := false
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var _player: Node3D
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func _ready():
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add_to_group("AGENT")
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func init(player: Node3D):
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_player = player
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#-- Methods that need implementing using the "extend script" option in Godot --#
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func get_obs() -> Dictionary:
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assert(false, "the get_obs method is not implemented when extending from ai_controller")
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return {"obs": []}
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func get_reward() -> float:
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assert(false, "the get_reward method is not implemented when extending from ai_controller")
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return 0.0
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func get_action_space() -> Dictionary:
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assert(
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false,
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"the get_action_space method is not implemented when extending from ai_controller"
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)
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return {
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"example_actions_continous": {"size": 2, "action_type": "continuous"},
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"example_actions_discrete": {"size": 2, "action_type": "discrete"},
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}
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func set_action(action) -> void:
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assert(false, "the set_action method is not implemented when extending from ai_controller")
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#-----------------------------------------------------------------------------#
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#-- Methods that sometimes need implementing using the "extend script" option in Godot --#
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# Only needed if you are recording expert demos with this AIController
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func get_action() -> Array:
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assert(false, "the get_action method is not implemented in extended AIController but demo_recorder is used")
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return []
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# -----------------------------------------------------------------------------#
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func _physics_process(delta):
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n_steps += 1
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if n_steps > reset_after:
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needs_reset = true
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func get_obs_space():
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# may need overriding if the obs space is complex
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var obs = get_obs()
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return {
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"obs": {"size": [len(obs["obs"])], "space": "box"},
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}
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func reset():
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n_steps = 0
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needs_reset = false
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func reset_if_done():
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if done:
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reset()
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func set_heuristic(h):
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# sets the heuristic from "human" or "model" nothing to change here
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heuristic = h
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func get_done():
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return done
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func set_done_false():
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done = false
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func zero_reward():
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reward = 0.0
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