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@@ -11,3 +11,38 @@ assets/sunflowers_puresky_2k.hdr filter=lfs diff=lfs merge=lfs -text
 bin/Ships.exe filter=lfs diff=lfs merge=lfs -text
 bin/Ships.pck filter=lfs diff=lfs merge=lfs -text
 bin/Ships.x86_64 filter=lfs diff=lfs merge=lfs -text
+bin/data_GridSensor3DExample_linuxbsd_x86_64/GodotSharp.dll filter=lfs diff=lfs merge=lfs -text
+bin/data_GridSensor3DExample_linuxbsd_x86_64/Microsoft.VisualBasic.Core.dll filter=lfs diff=lfs merge=lfs -text
+bin/data_GridSensor3DExample_linuxbsd_x86_64/System.Data.Common.dll filter=lfs diff=lfs merge=lfs -text
+bin/data_GridSensor3DExample_linuxbsd_x86_64/System.Linq.Expressions.dll filter=lfs diff=lfs merge=lfs -text
+bin/data_GridSensor3DExample_linuxbsd_x86_64/System.Net.Http.dll filter=lfs diff=lfs merge=lfs -text
+bin/data_GridSensor3DExample_linuxbsd_x86_64/System.Private.CoreLib.dll filter=lfs diff=lfs merge=lfs -text
+bin/data_GridSensor3DExample_linuxbsd_x86_64/System.Private.DataContractSerialization.dll filter=lfs diff=lfs merge=lfs -text
+bin/data_GridSensor3DExample_linuxbsd_x86_64/System.Private.Xml.dll filter=lfs diff=lfs merge=lfs -text
+bin/data_GridSensor3DExample_linuxbsd_x86_64/System.Reflection.Metadata.dll filter=lfs diff=lfs merge=lfs -text
+bin/data_GridSensor3DExample_linuxbsd_x86_64/System.Text.Json.dll filter=lfs diff=lfs merge=lfs -text
+bin/data_GridSensor3DExample_linuxbsd_x86_64/libclrjit.so filter=lfs diff=lfs merge=lfs -text
+bin/data_GridSensor3DExample_linuxbsd_x86_64/libcoreclr.so filter=lfs diff=lfs merge=lfs -text
+bin/data_GridSensor3DExample_linuxbsd_x86_64/libmscordaccore.so filter=lfs diff=lfs merge=lfs -text
+bin/data_GridSensor3DExample_linuxbsd_x86_64/libmscordbi.so filter=lfs diff=lfs merge=lfs -text
+bin/data_GridSensor3DExample_linuxbsd_x86_64/libonnxruntime.so filter=lfs diff=lfs merge=lfs -text
+bin/data_GridSensor3DExample_linuxbsd_x86_64/onnxruntime.dll filter=lfs diff=lfs merge=lfs -text
+bin/data_GridSensor3DExample_windows_x86_64/GodotSharp.dll filter=lfs diff=lfs merge=lfs -text
+bin/data_GridSensor3DExample_windows_x86_64/Microsoft.CSharp.dll filter=lfs diff=lfs merge=lfs -text
+bin/data_GridSensor3DExample_windows_x86_64/Microsoft.DiaSymReader.Native.amd64.dll filter=lfs diff=lfs merge=lfs -text
+bin/data_GridSensor3DExample_windows_x86_64/Microsoft.VisualBasic.Core.dll filter=lfs diff=lfs merge=lfs -text
+bin/data_GridSensor3DExample_windows_x86_64/System.Data.Common.dll filter=lfs diff=lfs merge=lfs -text
+bin/data_GridSensor3DExample_windows_x86_64/System.Linq.Expressions.dll filter=lfs diff=lfs merge=lfs -text
+bin/data_GridSensor3DExample_windows_x86_64/System.Net.Http.dll filter=lfs diff=lfs merge=lfs -text
+bin/data_GridSensor3DExample_windows_x86_64/System.Private.CoreLib.dll filter=lfs diff=lfs merge=lfs -text
+bin/data_GridSensor3DExample_windows_x86_64/System.Private.DataContractSerialization.dll filter=lfs diff=lfs merge=lfs -text
+bin/data_GridSensor3DExample_windows_x86_64/System.Private.Xml.dll filter=lfs diff=lfs merge=lfs -text
+bin/data_GridSensor3DExample_windows_x86_64/System.Reflection.Metadata.dll filter=lfs diff=lfs merge=lfs -text
+bin/data_GridSensor3DExample_windows_x86_64/System.Text.Json.dll filter=lfs diff=lfs merge=lfs -text
+bin/data_GridSensor3DExample_windows_x86_64/clrjit.dll filter=lfs diff=lfs merge=lfs -text
+bin/data_GridSensor3DExample_windows_x86_64/coreclr.dll filter=lfs diff=lfs merge=lfs -text
+bin/data_GridSensor3DExample_windows_x86_64/mscordaccore.dll filter=lfs diff=lfs merge=lfs -text
+bin/data_GridSensor3DExample_windows_x86_64/mscordaccore_amd64_amd64_6.0.2724.6912.dll filter=lfs diff=lfs merge=lfs -text
+bin/data_GridSensor3DExample_windows_x86_64/mscordbi.dll filter=lfs diff=lfs merge=lfs -text
+bin/data_GridSensor3DExample_windows_x86_64/onnxruntime.dll filter=lfs diff=lfs merge=lfs -text
+bin/data_GridSensor3DExample_windows_x86_64/ucrtbase.dll filter=lfs diff=lfs merge=lfs -text

GridSensor3DExample.csproj.old

@@ -1,4 +1,4 @@
-<Project Sdk="Godot.NET.Sdk/4.2.0">
+<Project Sdk="Godot.NET.Sdk/4.0.3">
   <PropertyGroup>
     <TargetFramework>net6.0</TargetFramework>
     <EnableDynamicLoading>true</EnableDynamicLoading>

GridSensor3DExample.sln

@@ -0,0 +1,25 @@
+
+Microsoft Visual Studio Solution File, Format Version 12.00
+# Visual Studio Version 17
+VisualStudioVersion = 17.5.33530.505
+MinimumVisualStudioVersion = 10.0.40219.1
+Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "Godot RL Agents", "Godot RL Agents.csproj", "{055E8CBC-A3EC-41A8-BC53-EC3010682AE4}"
+EndProject
+Global
+	GlobalSection(SolutionConfigurationPlatforms) = preSolution
+		Debug|Any CPU = Debug|Any CPU
+		ExportDebug|Any CPU = ExportDebug|Any CPU
+		ExportRelease|Any CPU = ExportRelease|Any CPU
+	EndGlobalSection
+	GlobalSection(ProjectConfigurationPlatforms) = postSolution
+		{055E8CBC-A3EC-41A8-BC53-EC3010682AE4}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
+		{055E8CBC-A3EC-41A8-BC53-EC3010682AE4}.Debug|Any CPU.Build.0 = Debug|Any CPU
+		{055E8CBC-A3EC-41A8-BC53-EC3010682AE4}.ExportDebug|Any CPU.ActiveCfg = ExportDebug|Any CPU
+		{055E8CBC-A3EC-41A8-BC53-EC3010682AE4}.ExportDebug|Any CPU.Build.0 = ExportDebug|Any CPU
+		{055E8CBC-A3EC-41A8-BC53-EC3010682AE4}.ExportRelease|Any CPU.ActiveCfg = ExportRelease|Any CPU
+		{055E8CBC-A3EC-41A8-BC53-EC3010682AE4}.ExportRelease|Any CPU.Build.0 = ExportRelease|Any CPU
+	EndGlobalSection
+	GlobalSection(SolutionProperties) = preSolution
+		HideSolutionNode = FALSE
+	EndGlobalSection
+EndGlobal

addons/godot_rl_agents/controller/ai_controller_2d.gd

@@ -1,8 +1,23 @@
 extends Node2D
 class_name AIController2D
 
+enum ControlModes { INHERIT_FROM_SYNC, HUMAN, TRAINING, ONNX_INFERENCE, RECORD_EXPERT_DEMOS }
+@export var control_mode: ControlModes = ControlModes.INHERIT_FROM_SYNC
+@export var onnx_model_path := ""
 @export var reset_after := 1000
 
+@export_group("Record expert demos mode options")
+## Path where the demos will be saved. The file can later be used for imitation learning.
+@export var expert_demo_save_path: String
+## The action that erases the last recorded episode from the currently recorded data.
+@export var remove_last_episode_key: InputEvent
+## Action will be repeated for n frames. Will introduce control lag if larger than 1.
+## Can be used to ensure that action_repeat on inference and training matches
+## the recorded demonstrations.
+@export var action_repeat: int = 1
+
+var onnx_model: ONNXModel
+
 var heuristic := "human"
 var done := false
 var reward := 0.0
@@ -11,72 +26,88 @@ var needs_reset := false
 
 var _player: Node2D
 
+
 func _ready():
 	add_to_group("AGENT")
-	
+
+
 func init(player: Node2D):
 	_player = player
-	
+
+
 #-- Methods that need implementing using the "extend script" option in Godot --#
 func get_obs() -> Dictionary:
-	assert(false, "the get_obs method is not implemented when extending from ai_controller") 
-	return {"obs":[]}
+	assert(false, "the get_obs method is not implemented when extending from ai_controller")
+	return {"obs": []}
+
 
-func get_reward() -> float:	
-	assert(false, "the get_reward method is not implemented when extending from ai_controller") 
+func get_reward() -> float:
+	assert(false, "the get_reward method is not implemented when extending from ai_controller")
 	return 0.0
-	
+
+
 func get_action_space() -> Dictionary:
-	assert(false, "the get get_action_space method is not implemented when extending from ai_controller") 
+	assert(
+		false,
+		"the get get_action_space method is not implemented when extending from ai_controller"
+	)
 	return {
-		"example_actions_continous" : {
-			"size": 2,
-			"action_type": "continuous"
-		},
-		"example_actions_discrete" : {
-			"size": 2,
-			"action_type": "discrete"
-		},
-		}
-	
-func set_action(action) -> void:	
-	assert(false, "the get set_action method is not implemented when extending from ai_controller") 	
+		"example_actions_continous": {"size": 2, "action_type": "continuous"},
+		"example_actions_discrete": {"size": 2, "action_type": "discrete"},
+	}
+
+
+func set_action(action) -> void:
+	assert(false, "the get set_action method is not implemented when extending from ai_controller")
+
+
+#-----------------------------------------------------------------------------#
+
+
+#-- Methods that sometimes need implementing using the "extend script" option in Godot --#
+# Only needed if you are recording expert demos with this AIController
+func get_action() -> Array:
+	assert(false, "the get set_action method is not implemented in extended AIController but demo_recorder is used")
+	return []
+
 # -----------------------------------------------------------------------------#
-	
+
 func _physics_process(delta):
 	n_steps += 1
 	if n_steps > reset_after:
 		needs_reset = true
-		
+
+
 func get_obs_space():
 	# may need overriding if the obs space is complex
 	var obs = get_obs()
 	return {
-		"obs": {
-			"size": [len(obs["obs"])],
-			"space": "box"
-		},
+		"obs": {"size": [len(obs["obs"])], "space": "box"},
 	}
 
+
 func reset():
 	n_steps = 0
 	needs_reset = false
 
+
 func reset_if_done():
 	if done:
 		reset()
-		
+
+
 func set_heuristic(h):
 	# sets the heuristic from "human" or "model" nothing to change here
 	heuristic = h
 
+
 func get_done():
 	return done
-	
+
+
 func set_done_false():
 	done = false
 
+
 func zero_reward():
 	reward = 0.0
-	
-

addons/godot_rl_agents/controller/ai_controller_3d.gd

@@ -1,8 +1,23 @@
 extends Node3D
 class_name AIController3D
 
+enum ControlModes { INHERIT_FROM_SYNC, HUMAN, TRAINING, ONNX_INFERENCE, RECORD_EXPERT_DEMOS }
+@export var control_mode: ControlModes = ControlModes.INHERIT_FROM_SYNC
+@export var onnx_model_path := ""
 @export var reset_after := 1000
 
+@export_group("Record expert demos mode options")
+## Path where the demos will be saved. The file can later be used for imitation learning.
+@export var expert_demo_save_path: String
+## The action that erases the last recorded episode from the currently recorded data.
+@export var remove_last_episode_key: InputEvent
+## Action will be repeated for n frames. Will introduce control lag if larger than 1.
+## Can be used to ensure that action_repeat on inference and training matches
+## the recorded demonstrations.
+@export var action_repeat: int = 1
+
+var onnx_model: ONNXModel
+
 var heuristic := "human"
 var done := false
 var reward := 0.0
@@ -11,70 +26,89 @@ var needs_reset := false
 
 var _player: Node3D
 
+
 func _ready():
 	add_to_group("AGENT")
-	
+
+
 func init(player: Node3D):
 	_player = player
-	
+
+
 #-- Methods that need implementing using the "extend script" option in Godot --#
 func get_obs() -> Dictionary:
-	assert(false, "the get_obs method is not implemented when extending from ai_controller") 
-	return {"obs":[]}
+	assert(false, "the get_obs method is not implemented when extending from ai_controller")
+	return {"obs": []}
+
 
-func get_reward() -> float:	
-	assert(false, "the get_reward method is not implemented when extending from ai_controller") 
+func get_reward() -> float:
+	assert(false, "the get_reward method is not implemented when extending from ai_controller")
 	return 0.0
-	
+
+
 func get_action_space() -> Dictionary:
-	assert(false, "the get get_action_space method is not implemented when extending from ai_controller") 
+	assert(
+		false,
+		"the get get_action_space method is not implemented when extending from ai_controller"
+	)
 	return {
-		"example_actions_continous" : {
-			"size": 2,
-			"action_type": "continuous"
-		},
-		"example_actions_discrete" : {
-			"size": 2,
-			"action_type": "discrete"
-		},
-		}
-	
-func set_action(action) -> void:	
-	assert(false, "the get set_action method is not implemented when extending from ai_controller") 	
+		"example_actions_continous": {"size": 2, "action_type": "continuous"},
+		"example_actions_discrete": {"size": 2, "action_type": "discrete"},
+	}
+
+
+func set_action(action) -> void:
+	assert(false, "the get set_action method is not implemented when extending from ai_controller")
+
+
+#-----------------------------------------------------------------------------#
+
+
+#-- Methods that sometimes need implementing using the "extend script" option in Godot --#
+# Only needed if you are recording expert demos with this AIController
+func get_action() -> Array:
+	assert(false, "the get set_action method is not implemented in extended AIController but demo_recorder is used")
+	return []
+
 # -----------------------------------------------------------------------------#
-	
+
+
 func _physics_process(delta):
 	n_steps += 1
 	if n_steps > reset_after:
 		needs_reset = true
-		
+
+
 func get_obs_space():
 	# may need overriding if the obs space is complex
 	var obs = get_obs()
 	return {
-		"obs": {
-			"size": [len(obs["obs"])],
-			"space": "box"
-		},
+		"obs": {"size": [len(obs["obs"])], "space": "box"},
 	}
 
+
 func reset():
 	n_steps = 0
 	needs_reset = false
 
+
 func reset_if_done():
 	if done:
 		reset()
-		
+
+
 func set_heuristic(h):
 	# sets the heuristic from "human" or "model" nothing to change here
 	heuristic = h
 
+
 func get_done():
 	return done
-	
+
+
 func set_done_false():
 	done = false
 
+
 func zero_reward():
 	reward = 0.0

addons/godot_rl_agents/onnx/wrapper/ONNX_wrapper.gd

@@ -4,20 +4,23 @@ var inferencer_script = load("res://addons/godot_rl_agents/onnx/csharp/ONNXInfer
 
 var inferencer = null
 
+
 # Must provide the path to the model and the batch size
 func _init(model_path, batch_size):
 	inferencer = inferencer_script.new()
 	inferencer.Initialize(model_path, batch_size)
 
-# This function is the one that will be called from the game, 
+
+# This function is the one that will be called from the game,
 # requires the observation as an array and the state_ins as an int
-# returns an Array containing the action the model takes. 
-func run_inference(obs : Array, state_ins : int) -> Dictionary:
+# returns an Array containing the action the model takes.
+func run_inference(obs: Array, state_ins: int) -> Dictionary:
 	if inferencer == null:
 		printerr("Inferencer not initialized")
 		return {}
 	return inferencer.RunInference(obs, state_ins)
 
+
 func _notification(what):
 	if what == NOTIFICATION_PREDELETE:
 		inferencer.FreeDisposables()

addons/godot_rl_agents/sensors/sensors_2d/GridSensor2D.gd

@@ -3,49 +3,57 @@ extends ISensor2D
 class_name GridSensor2D
 
 @export var debug_view := false:
-	get: return debug_view
+	get:
+		return debug_view
 	set(value):
 		debug_view = value
 		_update()
-		
+
 @export_flags_2d_physics var detection_mask := 0:
-	get: return detection_mask
+	get:
+		return detection_mask
 	set(value):
 		detection_mask = value
 		_update()
 
 @export var collide_with_areas := false:
-	get: return collide_with_areas
+	get:
+		return collide_with_areas
 	set(value):
 		collide_with_areas = value
 		_update()
 
 @export var collide_with_bodies := true:
-	get: return collide_with_bodies
+	get:
+		return collide_with_bodies
 	set(value):
 		collide_with_bodies = value
 		_update()
 
 @export_range(1, 200, 0.1) var cell_width := 20.0:
-	get: return cell_width
+	get:
+		return cell_width
 	set(value):
 		cell_width = value
 		_update()
 
 @export_range(1, 200, 0.1) var cell_height := 20.0:
-	get: return cell_height
+	get:
+		return cell_height
 	set(value):
 		cell_height = value
-		_update()	
+		_update()
 
 @export_range(1, 21, 2, "or_greater") var grid_size_x := 3:
-	get: return grid_size_x
+	get:
+		return grid_size_x
 	set(value):
 		grid_size_x = value
 		_update()
 
 @export_range(1, 21, 2, "or_greater") var grid_size_y := 3:
-	get: return grid_size_y
+	get:
+		return grid_size_y
 	set(value):
 		grid_size_y = value
 		_update()
@@ -58,158 +66,169 @@ var _n_layers_per_cell: int
 var _highlighted_cell_color: Color
 var _standard_cell_color: Color
 
+
 func get_observation():
 	return _obs_buffer
-	
+
+
 func _update():
 	if Engine.is_editor_hint():
 		if is_node_ready():
-			_spawn_nodes()	
+			_spawn_nodes()
+
 
 func _ready() -> void:
 	_set_colors()
-	
-	if Engine.is_editor_hint():	
+
+	if Engine.is_editor_hint():
 		if get_child_count() == 0:
 			_spawn_nodes()
 	else:
 		_spawn_nodes()
-		
-	
+
+
 func _set_colors() -> void:
-	_standard_cell_color = Color(100.0/255.0, 100.0/255.0, 100.0/255.0, 100.0/255.0)
-	_highlighted_cell_color = Color(255.0/255.0, 100.0/255.0, 100.0/255.0, 100.0/255.0)
+	_standard_cell_color = Color(100.0 / 255.0, 100.0 / 255.0, 100.0 / 255.0, 100.0 / 255.0)
+	_highlighted_cell_color = Color(255.0 / 255.0, 100.0 / 255.0, 100.0 / 255.0, 100.0 / 255.0)
+
 
 func _get_collision_mapping() -> Dictionary:
 	# defines which layer is mapped to which cell obs index
 	var total_bits = 0
-	var collision_mapping = {} 
+	var collision_mapping = {}
 	for i in 32:
-		var bit_mask = 2**i
+		var bit_mask = 2 ** i
 		if (detection_mask & bit_mask) > 0:
 			collision_mapping[i] = total_bits
 			total_bits += 1
-		
+
 	return collision_mapping
 
+
 func _spawn_nodes():
 	for cell in get_children():
-		cell.name = "_%s" % cell.name # Otherwise naming below will fail
+		cell.name = "_%s" % cell.name  # Otherwise naming below will fail
 		cell.queue_free()
-	
+
 	_collision_mapping = _get_collision_mapping()
 	#prints("collision_mapping", _collision_mapping, len(_collision_mapping))
 	# allocate memory for the observations
 	_n_layers_per_cell = len(_collision_mapping)
 	_obs_buffer = PackedFloat64Array()
-	_obs_buffer.resize(grid_size_x*grid_size_y*_n_layers_per_cell)
+	_obs_buffer.resize(grid_size_x * grid_size_y * _n_layers_per_cell)
 	_obs_buffer.fill(0)
 	#prints(len(_obs_buffer), _obs_buffer )
-	
+
 	_rectangle_shape = RectangleShape2D.new()
 	_rectangle_shape.set_size(Vector2(cell_width, cell_height))
-	
+
 	var shift := Vector2(
-		-(grid_size_x/2)*cell_width,
-		-(grid_size_y/2)*cell_height,
+		-(grid_size_x / 2) * cell_width,
+		-(grid_size_y / 2) * cell_height,
 	)
-	
+
 	for i in grid_size_x:
 		for j in grid_size_y:
-			var cell_position =  Vector2(i*cell_width, j*cell_height) + shift
+			var cell_position = Vector2(i * cell_width, j * cell_height) + shift
 			_create_cell(i, j, cell_position)
-		
 
-func _create_cell(i:int, j:int, position: Vector2):
-	var cell : = Area2D.new()
+
+func _create_cell(i: int, j: int, position: Vector2):
+	var cell := Area2D.new()
 	cell.position = position
-	cell.name = "GridCell %s %s" %[i, j]
+	cell.name = "GridCell %s %s" % [i, j]
 	cell.modulate = _standard_cell_color
-	
+
 	if collide_with_areas:
 		cell.area_entered.connect(_on_cell_area_entered.bind(i, j))
 		cell.area_exited.connect(_on_cell_area_exited.bind(i, j))
-		
+
 	if collide_with_bodies:
 		cell.body_entered.connect(_on_cell_body_entered.bind(i, j))
 		cell.body_exited.connect(_on_cell_body_exited.bind(i, j))
-	
+
 	cell.collision_layer = 0
 	cell.collision_mask = detection_mask
 	cell.monitorable = true
 	add_child(cell)
 	cell.set_owner(get_tree().edited_scene_root)
 
-	var col_shape : = CollisionShape2D.new()
+	var col_shape := CollisionShape2D.new()
 	col_shape.shape = _rectangle_shape
 	col_shape.name = "CollisionShape2D"
 	cell.add_child(col_shape)
 	col_shape.set_owner(get_tree().edited_scene_root)
-	
+
 	if debug_view:
 		var quad = MeshInstance2D.new()
 		quad.name = "MeshInstance2D"
 		var quad_mesh = QuadMesh.new()
-		
+
 		quad_mesh.set_size(Vector2(cell_width, cell_height))
-		
+
 		quad.mesh = quad_mesh
 		cell.add_child(quad)
 		quad.set_owner(get_tree().edited_scene_root)
 
-func _update_obs(cell_i:int, cell_j:int, collision_layer:int, entered: bool):
+
+func _update_obs(cell_i: int, cell_j: int, collision_layer: int, entered: bool):
 	for key in _collision_mapping:
-		var bit_mask = 2**key
+		var bit_mask = 2 ** key
 		if (collision_layer & bit_mask) > 0:
 			var collison_map_index = _collision_mapping[key]
-			
+
 			var obs_index = (
-							(cell_i * grid_size_x * _n_layers_per_cell) + 
-							(cell_j * _n_layers_per_cell) + 
-							collison_map_index
-							)
+				(cell_i * grid_size_x * _n_layers_per_cell)
+				+ (cell_j * _n_layers_per_cell)
+				+ collison_map_index
+			)
 			#prints(obs_index, cell_i, cell_j)
 			if entered:
 				_obs_buffer[obs_index] += 1
 			else:
 				_obs_buffer[obs_index] -= 1
 
-func _toggle_cell(cell_i:int, cell_j:int):
-	var cell = get_node_or_null("GridCell %s %s" %[cell_i, cell_j])
-	
+
+func _toggle_cell(cell_i: int, cell_j: int):
+	var cell = get_node_or_null("GridCell %s %s" % [cell_i, cell_j])
+
 	if cell == null:
 		print("cell not found, returning")
-		
+
 	var n_hits = 0
 	var start_index = (cell_i * grid_size_x * _n_layers_per_cell) + (cell_j * _n_layers_per_cell)
 	for i in _n_layers_per_cell:
-		n_hits += _obs_buffer[start_index+i]
-		
+		n_hits += _obs_buffer[start_index + i]
+
 	if n_hits > 0:
 		cell.modulate = _highlighted_cell_color
 	else:
 		cell.modulate = _standard_cell_color
-		
-func _on_cell_area_entered(area:Area2D, cell_i:int, cell_j:int):
+
+
+func _on_cell_area_entered(area: Area2D, cell_i: int, cell_j: int):
 	#prints("_on_cell_area_entered", cell_i, cell_j)
 	_update_obs(cell_i, cell_j, area.collision_layer, true)
 	if debug_view:
 		_toggle_cell(cell_i, cell_j)
 	#print(_obs_buffer)
 
-func _on_cell_area_exited(area:Area2D, cell_i:int, cell_j:int):
+
+func _on_cell_area_exited(area: Area2D, cell_i: int, cell_j: int):
 	#prints("_on_cell_area_exited", cell_i, cell_j)
 	_update_obs(cell_i, cell_j, area.collision_layer, false)
 	if debug_view:
 		_toggle_cell(cell_i, cell_j)
 
-func _on_cell_body_entered(body: Node2D, cell_i:int, cell_j:int):
+
+func _on_cell_body_entered(body: Node2D, cell_i: int, cell_j: int):
 	#prints("_on_cell_body_entered", cell_i, cell_j)
 	_update_obs(cell_i, cell_j, body.collision_layer, true)
 	if debug_view:
 		_toggle_cell(cell_i, cell_j)
 
-func _on_cell_body_exited(body: Node2D, cell_i:int, cell_j:int):
+
+func _on_cell_body_exited(body: Node2D, cell_i: int, cell_j: int):
 	#prints("_on_cell_body_exited", cell_i, cell_j)
 	_update_obs(cell_i, cell_j, body.collision_layer, false)
 	if debug_view:

addons/godot_rl_agents/sensors/sensors_2d/ISensor2D.gd

@@ -1,20 +1,25 @@
 extends Node2D
 class_name ISensor2D
 
-var _obs : Array = []
+var _obs: Array = []
 var _active := false
 
+
 func get_observation():
 	pass
-	
+
+
 func activate():
 	_active = true
-	
+
+
 func deactivate():
 	_active = false
 
+
 func _update_observation():
 	pass
-	
+
+
 func reset():
 	pass

addons/godot_rl_agents/sensors/sensors_2d/RaycastSensor2D.gd

@@ -3,50 +3,57 @@ extends ISensor2D
 class_name RaycastSensor2D
 
 @export_flags_2d_physics var collision_mask := 1:
-	get: return collision_mask
+	get:
+		return collision_mask
 	set(value):
 		collision_mask = value
 		_update()
 
 @export var collide_with_areas := false:
-	get: return collide_with_areas
+	get:
+		return collide_with_areas
 	set(value):
 		collide_with_areas = value
 		_update()
 
 @export var collide_with_bodies := true:
-	get: return collide_with_bodies
+	get:
+		return collide_with_bodies
 	set(value):
 		collide_with_bodies = value
 		_update()
 
 @export var n_rays := 16.0:
-	get: return n_rays
+	get:
+		return n_rays
 	set(value):
 		n_rays = value
 		_update()
-	
-@export_range(5,200,5.0) var ray_length := 200:
-	get: return ray_length
+
+@export_range(5, 3000, 5.0) var ray_length := 200:
+	get:
+		return ray_length
 	set(value):
 		ray_length = value
 		_update()
-@export_range(5,360,5.0) var cone_width := 360.0:
-	get: return cone_width
+@export_range(5, 360, 5.0) var cone_width := 360.0:
+	get:
+		return cone_width
 	set(value):
 		cone_width = value
 		_update()
-	
-@export var debug_draw := true :
-	get: return debug_draw 
+
+@export var debug_draw := true:
+	get:
+		return debug_draw
 	set(value):
 		debug_draw = value
-		_update()  
-
+		_update()
 
 var _angles = []
 var rays := []
 
+
 func _update():
 	if Engine.is_editor_hint():
 		if debug_draw:
@@ -56,63 +63,56 @@ func _update():
 				if ray is RayCast2D:
 					remove_child(ray)
 
+
 func _ready() -> void:
 	_spawn_nodes()
 
+
 func _spawn_nodes():
 	for ray in rays:
 		ray.queue_free()
 	rays = []
-		
+
 	_angles = []
 	var step = cone_width / (n_rays)
-	var start = step/2 - cone_width/2
-	
+	var start = step / 2 - cone_width / 2
+
 	for i in n_rays:
 		var angle = start + i * step
 		var ray = RayCast2D.new()
-		ray.set_target_position(Vector2(
-			ray_length*cos(deg_to_rad(angle)),
-			ray_length*sin(deg_to_rad(angle))
-		))
-		ray.set_name("node_"+str(i))
-		ray.enabled  = true
+		ray.set_target_position(
+			Vector2(ray_length * cos(deg_to_rad(angle)), ray_length * sin(deg_to_rad(angle)))
+		)
+		ray.set_name("node_" + str(i))
+		ray.enabled = false
 		ray.collide_with_areas = collide_with_areas
 		ray.collide_with_bodies = collide_with_bodies
 		ray.collision_mask = collision_mask
 		add_child(ray)
 		rays.append(ray)
-		
-		
+
 		_angles.append(start + i * step)
-	
 
-func _physics_process(delta: float) -> void:
-	if self._active:
-		self._obs = calculate_raycasts()
-		
+
 func get_observation() -> Array:
-	if len(self._obs) == 0:
-		print("obs was null, forcing raycast update")
-		return self.calculate_raycasts()
-	return self._obs
-	
+	return self.calculate_raycasts()
+
 
 func calculate_raycasts() -> Array:
 	var result = []
 	for ray in rays:
+		ray.enabled = true
 		ray.force_raycast_update()
 		var distance = _get_raycast_distance(ray)
 		result.append(distance)
+		ray.enabled = false
 	return result
 
-func _get_raycast_distance(ray : RayCast2D) -> float : 
+
+func _get_raycast_distance(ray: RayCast2D) -> float:
 	if !ray.is_colliding():
 		return 0.0
-		
+
 	var distance = (global_position - ray.get_collision_point()).length()
 	distance = clamp(distance, 0.0, ray_length)
 	return (ray_length - distance) / ray_length
-	
-	
-	

addons/godot_rl_agents/sensors/sensors_3d/GridSensor3D.gd

@@ -3,50 +3,58 @@ extends ISensor3D
 class_name GridSensor3D
 
 @export var debug_view := false:
-	get: return debug_view
+	get:
+		return debug_view
 	set(value):
 		debug_view = value
 		_update()
-		
+
 @export_flags_3d_physics var detection_mask := 0:
-	get: return detection_mask
+	get:
+		return detection_mask
 	set(value):
 		detection_mask = value
 		_update()
 
 @export var collide_with_areas := false:
-	get: return collide_with_areas
+	get:
+		return collide_with_areas
 	set(value):
 		collide_with_areas = value
 		_update()
 
 @export var collide_with_bodies := false:
 	# NOTE! The sensor will not detect StaticBody3D, add an area to static bodies to detect them
-	get: return collide_with_bodies
+	get:
+		return collide_with_bodies
 	set(value):
 		collide_with_bodies = value
 		_update()
 
 @export_range(0.1, 2, 0.1) var cell_width := 1.0:
-	get: return cell_width
+	get:
+		return cell_width
 	set(value):
 		cell_width = value
 		_update()
 
 @export_range(0.1, 2, 0.1) var cell_height := 1.0:
-	get: return cell_height
+	get:
+		return cell_height
 	set(value):
 		cell_height = value
-		_update()	
+		_update()
 
 @export_range(1, 21, 2, "or_greater") var grid_size_x := 3:
-	get: return grid_size_x
+	get:
+		return grid_size_x
 	set(value):
 		grid_size_x = value
 		_update()
 
 @export_range(1, 21, 2, "or_greater") var grid_size_z := 3:
-	get: return grid_size_z
+	get:
+		return grid_size_z
 	set(value):
 		grid_size_z = value
 		_update()
@@ -59,95 +67,106 @@ var _n_layers_per_cell: int
 var _highlighted_box_material: StandardMaterial3D
 var _standard_box_material: StandardMaterial3D
 
+
 func get_observation():
 	return _obs_buffer
 
+
 func reset():
 	_obs_buffer.fill(0)
 
+
 func _update():
 	if Engine.is_editor_hint():
 		if is_node_ready():
-			_spawn_nodes()	
+			_spawn_nodes()
+
 
 func _ready() -> void:
 	_make_materials()
-	
-	if Engine.is_editor_hint():	
+
+	if Engine.is_editor_hint():
 		if get_child_count() == 0:
 			_spawn_nodes()
 	else:
 		_spawn_nodes()
-	
+
+
 func _make_materials() -> void:
 	if _highlighted_box_material != null and _standard_box_material != null:
 		return
-		
+
 	_standard_box_material = StandardMaterial3D.new()
-	_standard_box_material.set_transparency(1) # ALPHA
-	_standard_box_material.albedo_color = Color(100.0/255.0, 100.0/255.0, 100.0/255.0, 100.0/255.0)
-	
+	_standard_box_material.set_transparency(1)  # ALPHA
+	_standard_box_material.albedo_color = Color(
+		100.0 / 255.0, 100.0 / 255.0, 100.0 / 255.0, 100.0 / 255.0
+	)
+
 	_highlighted_box_material = StandardMaterial3D.new()
-	_highlighted_box_material.set_transparency(1) # ALPHA
-	_highlighted_box_material.albedo_color = Color(255.0/255.0, 100.0/255.0, 100.0/255.0, 100.0/255.0)
+	_highlighted_box_material.set_transparency(1)  # ALPHA
+	_highlighted_box_material.albedo_color = Color(
+		255.0 / 255.0, 100.0 / 255.0, 100.0 / 255.0, 100.0 / 255.0
+	)
+
 
 func _get_collision_mapping() -> Dictionary:
 	# defines which layer is mapped to which cell obs index
 	var total_bits = 0
-	var collision_mapping = {} 
+	var collision_mapping = {}
 	for i in 32:
-		var bit_mask = 2**i
+		var bit_mask = 2 ** i
 		if (detection_mask & bit_mask) > 0:
 			collision_mapping[i] = total_bits
 			total_bits += 1
-		
+
 	return collision_mapping
 
+
 func _spawn_nodes():
 	for cell in get_children():
-		cell.name = "_%s" % cell.name # Otherwise naming below will fail
+		cell.name = "_%s" % cell.name  # Otherwise naming below will fail
 		cell.queue_free()
-	
+
 	_collision_mapping = _get_collision_mapping()
 	#prints("collision_mapping", _collision_mapping, len(_collision_mapping))
 	# allocate memory for the observations
 	_n_layers_per_cell = len(_collision_mapping)
 	_obs_buffer = PackedFloat64Array()
-	_obs_buffer.resize(grid_size_x*grid_size_z*_n_layers_per_cell)
+	_obs_buffer.resize(grid_size_x * grid_size_z * _n_layers_per_cell)
 	_obs_buffer.fill(0)
 	#prints(len(_obs_buffer), _obs_buffer )
-	
+
 	_box_shape = BoxShape3D.new()
 	_box_shape.set_size(Vector3(cell_width, cell_height, cell_width))
-	
+
 	var shift := Vector3(
-		-(grid_size_x/2)*cell_width,
+		-(grid_size_x / 2) * cell_width,
 		0,
-		-(grid_size_z/2)*cell_width,
+		-(grid_size_z / 2) * cell_width,
 	)
-	
+
 	for i in grid_size_x:
 		for j in grid_size_z:
-			var cell_position =  Vector3(i*cell_width, 0.0, j*cell_width) + shift
+			var cell_position = Vector3(i * cell_width, 0.0, j * cell_width) + shift
 			_create_cell(i, j, cell_position)
-		
 
-func _create_cell(i:int, j:int, position: Vector3):
-	var cell : = Area3D.new()
+
+func _create_cell(i: int, j: int, position: Vector3):
+	var cell := Area3D.new()
 	cell.position = position
-	cell.name = "GridCell %s %s" %[i, j]
-	
+	cell.name = "GridCell %s %s" % [i, j]
+
 	if collide_with_areas:
 		cell.area_entered.connect(_on_cell_area_entered.bind(i, j))
 		cell.area_exited.connect(_on_cell_area_exited.bind(i, j))
-		
+
 	if collide_with_bodies:
 		cell.body_entered.connect(_on_cell_body_entered.bind(i, j))
 		cell.body_exited.connect(_on_cell_body_exited.bind(i, j))
-		
+
 #		cell.body_shape_entered.connect(_on_cell_body_shape_entered.bind(i, j))
 #		cell.body_shape_exited.connect(_on_cell_body_shape_exited.bind(i, j))
-	
+
 	cell.collision_layer = 0
 	cell.collision_mask = detection_mask
 	cell.monitorable = true
@@ -155,78 +174,84 @@ func _create_cell(i:int, j:int, position: Vector3):
 	add_child(cell)
 	cell.set_owner(get_tree().edited_scene_root)
 
-	var col_shape : = CollisionShape3D.new()
+	var col_shape := CollisionShape3D.new()
 	col_shape.shape = _box_shape
 	col_shape.name = "CollisionShape3D"
 	cell.add_child(col_shape)
 	col_shape.set_owner(get_tree().edited_scene_root)
-	
+
 	if debug_view:
 		var box = MeshInstance3D.new()
 		box.name = "MeshInstance3D"
 		var box_mesh = BoxMesh.new()
-		
+
 		box_mesh.set_size(Vector3(cell_width, cell_height, cell_width))
 		box_mesh.material = _standard_box_material
-		
+
 		box.mesh = box_mesh
 		cell.add_child(box)
 		box.set_owner(get_tree().edited_scene_root)
 
-func _update_obs(cell_i:int, cell_j:int, collision_layer:int, entered: bool):
+
+func _update_obs(cell_i: int, cell_j: int, collision_layer: int, entered: bool):
 	for key in _collision_mapping:
-		var bit_mask = 2**key
+		var bit_mask = 2 ** key
 		if (collision_layer & bit_mask) > 0:
 			var collison_map_index = _collision_mapping[key]
-			
+
 			var obs_index = (
-							(cell_i * grid_size_x * _n_layers_per_cell) + 
-							(cell_j * _n_layers_per_cell) + 
-							collison_map_index
-							)
+				(cell_i * grid_size_x * _n_layers_per_cell)
+				+ (cell_j * _n_layers_per_cell)
+				+ collison_map_index
+			)
 			#prints(obs_index, cell_i, cell_j)
 			if entered:
 				_obs_buffer[obs_index] += 1
 			else:
 				_obs_buffer[obs_index] -= 1
 
-func _toggle_cell(cell_i:int, cell_j:int):
-	var cell = get_node_or_null("GridCell %s %s" %[cell_i, cell_j])
-	
+
+func _toggle_cell(cell_i: int, cell_j: int):
+	var cell = get_node_or_null("GridCell %s %s" % [cell_i, cell_j])
+
 	if cell == null:
 		print("cell not found, returning")
-		
+
 	var n_hits = 0
 	var start_index = (cell_i * grid_size_x * _n_layers_per_cell) + (cell_j * _n_layers_per_cell)
 	for i in _n_layers_per_cell:
-		n_hits += _obs_buffer[start_index+i]
-		
+		n_hits += _obs_buffer[start_index + i]
+
 	var cell_mesh = cell.get_node_or_null("MeshInstance3D")
 	if n_hits > 0:
 		cell_mesh.mesh.material = _highlighted_box_material
 	else:
 		cell_mesh.mesh.material = _standard_box_material
-		
-func _on_cell_area_entered(area:Area3D, cell_i:int, cell_j:int):
+
+
+func _on_cell_area_entered(area: Area3D, cell_i: int, cell_j: int):
 	#prints("_on_cell_area_entered", cell_i, cell_j)
 	_update_obs(cell_i, cell_j, area.collision_layer, true)
 	if debug_view:
 		_toggle_cell(cell_i, cell_j)
 	#print(_obs_buffer)
 
-func _on_cell_area_exited(area:Area3D, cell_i:int, cell_j:int):
+
+func _on_cell_area_exited(area: Area3D, cell_i: int, cell_j: int):
 	#prints("_on_cell_area_exited", cell_i, cell_j)
 	_update_obs(cell_i, cell_j, area.collision_layer, false)
 	if debug_view:
 		_toggle_cell(cell_i, cell_j)
 
-func _on_cell_body_entered(body: Node3D, cell_i:int, cell_j:int):
+
+func _on_cell_body_entered(body: Node3D, cell_i: int, cell_j: int):
 	#prints("_on_cell_body_entered", cell_i, cell_j)
 	_update_obs(cell_i, cell_j, body.collision_layer, true)
 	if debug_view:
 		_toggle_cell(cell_i, cell_j)
 
-func _on_cell_body_exited(body: Node3D, cell_i:int, cell_j:int):
+
+func _on_cell_body_exited(body: Node3D, cell_i: int, cell_j: int):
 	#prints("_on_cell_body_exited", cell_i, cell_j)
 	_update_obs(cell_i, cell_j, body.collision_layer, false)
 	if debug_view:

addons/godot_rl_agents/sensors/sensors_3d/ISensor3D.gd

@@ -1,20 +1,25 @@
 extends Node3D
 class_name ISensor3D
 
-var _obs : Array = []
+var _obs: Array = []
 var _active := false
 
+
 func get_observation():
 	pass
-	
+
+
 func activate():
 	_active = true
-	
+
+
 func deactivate():
 	_active = false
 
+
 func _update_observation():
 	pass
-	
+
+
 func reset():
 	pass

addons/godot_rl_agents/sensors/sensors_3d/RGBCameraSensor3D.gd

@@ -3,9 +3,19 @@ class_name RGBCameraSensor3D
 var camera_pixels = null
 
 @onready var camera_texture := $Control/TextureRect/CameraTexture as Sprite2D
+@onready var sub_viewport := $SubViewport as SubViewport
+
 
 func get_camera_pixel_encoding():
-	return camera_texture.get_texture().get_data().data["data"].hex_encode()
+	return camera_texture.get_texture().get_image().get_data().hex_encode()
+
 
-func get_camera_shape()-> Array:
-	return [$SubViewport.size[0], $SubViewport.size[1], 4]
+func get_camera_shape() -> Array:
+	assert(
+		sub_viewport.size.x >= 36 and sub_viewport.size.y >= 36,
+		"SubViewport size must be 36x36 or larger."
+	)
+	if sub_viewport.transparent_bg:
+		return [4, sub_viewport.size.y, sub_viewport.size.x]
+	else:
+		return [3, sub_viewport.size.y, sub_viewport.size.x]

addons/godot_rl_agents/sensors/sensors_3d/RaycastSensor3D.gd

@@ -2,75 +2,87 @@
 extends ISensor3D
 class_name RayCastSensor3D
 @export_flags_3d_physics var collision_mask = 1:
-	get: return collision_mask
+	get:
+		return collision_mask
 	set(value):
 		collision_mask = value
 		_update()
 @export_flags_3d_physics var boolean_class_mask = 1:
-	get: return boolean_class_mask
+	get:
+		return boolean_class_mask
 	set(value):
 		boolean_class_mask = value
 		_update()
 
 @export var n_rays_width := 6.0:
-	get: return n_rays_width
+	get:
+		return n_rays_width
 	set(value):
 		n_rays_width = value
 		_update()
-	
+
 @export var n_rays_height := 6.0:
-	get: return n_rays_height
+	get:
+		return n_rays_height
 	set(value):
 		n_rays_height = value
 		_update()
 
 @export var ray_length := 10.0:
-	get: return ray_length
+	get:
+		return ray_length
 	set(value):
 		ray_length = value
 		_update()
-		
+
 @export var cone_width := 60.0:
-	get: return cone_width
+	get:
+		return cone_width
 	set(value):
 		cone_width = value
 		_update()
-		
+
 @export var cone_height := 60.0:
-	get: return cone_height
+	get:
+		return cone_height
 	set(value):
 		cone_height = value
 		_update()
 
 @export var collide_with_areas := false:
-	get: return collide_with_areas
+	get:
+		return collide_with_areas
 	set(value):
 		collide_with_areas = value
 		_update()
-		
+
 @export var collide_with_bodies := true:
-	get: return collide_with_bodies
+	get:
+		return collide_with_bodies
 	set(value):
 		collide_with_bodies = value
 		_update()
 
 @export var class_sensor := false
-		
+
 var rays := []
 var geo = null
 
+
 func _update():
 	if Engine.is_editor_hint():
 		if is_node_ready():
-			_spawn_nodes()	
+			_spawn_nodes()
+
 
 func _ready() -> void:
-	if Engine.is_editor_hint():	
+	if Engine.is_editor_hint():
 		if get_child_count() == 0:
 			_spawn_nodes()
 	else:
 		_spawn_nodes()
 
+
 func _spawn_nodes():
 	print("spawning nodes")
 	for ray in get_children():
@@ -79,15 +91,15 @@ func _spawn_nodes():
 		geo.clear()
 	#$Lines.remove_points()
 	rays = []
-	
+
 	var horizontal_step = cone_width / (n_rays_width)
 	var vertical_step = cone_height / (n_rays_height)
-	
-	var horizontal_start = horizontal_step/2 - cone_width/2
-	var vertical_start = vertical_step/2 - cone_height/2   
+
+	var horizontal_start = horizontal_step / 2 - cone_width / 2
+	var vertical_start = vertical_step / 2 - cone_height / 2
 
 	var points = []
-	
+
 	for i in n_rays_width:
 		for j in n_rays_height:
 			var angle_w = horizontal_start + i * horizontal_step
@@ -98,9 +110,9 @@ func _spawn_nodes():
 			ray.set_target_position(cast_to)
 
 			points.append(cast_to)
-			
-			ray.set_name("node_"+str(i)+" "+str(j))
-			ray.enabled  = true
+
+			ray.set_name("node_" + str(i) + " " + str(j))
+			ray.enabled = true
 			ray.collide_with_bodies = collide_with_bodies
 			ray.collide_with_areas = collide_with_areas
 			ray.collision_mask = collision_mask
@@ -108,15 +120,17 @@ func _spawn_nodes():
 			ray.set_owner(get_tree().edited_scene_root)
 			rays.append(ray)
 			ray.force_raycast_update()
-			
+
+
 #    if Engine.editor_hint:
 #        _create_debug_lines(points)
-		
+
+
 func _create_debug_lines(points):
-	if not geo: 
+	if not geo:
 		geo = ImmediateMesh.new()
 		add_child(geo)
-		
+
 	geo.clear()
 	geo.begin(Mesh.PRIMITIVE_LINES)
 	for point in points:
@@ -125,20 +139,24 @@ func _create_debug_lines(points):
 		geo.add_vertex(point)
 	geo.end()
 
+
 func display():
 	if geo:
 		geo.display()
-	
+
+
 func to_spherical_coords(r, inc, azimuth) -> Vector3:
 	return Vector3(
-		r*sin(deg_to_rad(inc))*cos(deg_to_rad(azimuth)),
-		r*sin(deg_to_rad(azimuth)),
-		r*cos(deg_to_rad(inc))*cos(deg_to_rad(azimuth))       
+		r * sin(deg_to_rad(inc)) * cos(deg_to_rad(azimuth)),
+		r * sin(deg_to_rad(azimuth)),
+		r * cos(deg_to_rad(inc)) * cos(deg_to_rad(azimuth))
 	)
-	
+
+
 func get_observation() -> Array:
 	return self.calculate_raycasts()
 
+
 func calculate_raycasts() -> Array:
 	var result = []
 	for ray in rays:
@@ -148,19 +166,20 @@ func calculate_raycasts() -> Array:
 
 		result.append(distance)
 		if class_sensor:
-			var hit_class = 0 
+			var hit_class: float = 0
 			if ray.get_collider():
 				var hit_collision_layer = ray.get_collider().collision_layer
 				hit_collision_layer = hit_collision_layer & collision_mask
 				hit_class = (hit_collision_layer & boolean_class_mask) > 0
-			result.append(hit_class)
+			result.append(float(hit_class))
 		ray.set_enabled(false)
 	return result
 
-func _get_raycast_distance(ray : RayCast3D) -> float : 
+
+func _get_raycast_distance(ray: RayCast3D) -> float:
 	if !ray.is_colliding():
 		return 0.0
-		
+
 	var distance = (global_transform.origin - ray.get_collision_point()).length()
 	distance = clamp(distance, 0.0, ray_length)
 	return (ray_length - distance) / ray_length

addons/godot_rl_agents/sync.gd

@@ -2,23 +2,38 @@ extends Node
 
 # --fixed-fps 2000 --disable-render-loop
 
-enum ControlModes {HUMAN, TRAINING, ONNX_INFERENCE}
+enum ControlModes { HUMAN, TRAINING, ONNX_INFERENCE }
 @export var control_mode: ControlModes = ControlModes.TRAINING
 @export_range(1, 10, 1, "or_greater") var action_repeat := 8
-@export_range(1, 10, 1, "or_greater") var speed_up = 1
+@export_range(0, 10, 0.1, "or_greater") var speed_up := 1.0
 @export var onnx_model_path := ""
 
+# Onnx model stored for each requested path
+var onnx_models: Dictionary
+
 @onready var start_time = Time.get_ticks_msec()
 
 const MAJOR_VERSION := "0"
-const MINOR_VERSION := "3" 
+const MINOR_VERSION := "7" 
 const DEFAULT_PORT := "11008"
 const DEFAULT_SEED := "1"
-var stream : StreamPeerTCP = null
+var stream: StreamPeerTCP = null
 var connected = false
 var message_center
 var should_connect = true
-var agents
+
+var all_agents: Array
+var agents_training: Array
+var agents_inference: Array
+var agents_heuristic: Array
+
+## For recording expert demos
+var agent_demo_record: Node
+## Stores recorded trajectories
+var demo_trajectories: Array
+## A trajectory includes obs: Array, acts: Array, terminal (set in Python env instead)
+var current_demo_trajectory: Array
+
 var need_to_send_obs = false
 var args = null
 var initialized = false
@@ -26,141 +41,295 @@ var just_reset = false
 var onnx_model = null
 var n_action_steps = 0
 
-var _action_space : Dictionary
-var _obs_space : Dictionary
+var _action_space: Dictionary
+var _action_space_inference: Array[Dictionary] = []
+var _obs_space: Dictionary
+
 
 # Called when the node enters the scene tree for the first time.
 func _ready():
 	await get_tree().root.ready
-	get_tree().set_pause(true) 
+	get_tree().set_pause(true)
 	_initialize()
 	await get_tree().create_timer(1.0).timeout
-	get_tree().set_pause(false) 
-	
+	get_tree().set_pause(false)
+
+
 func _initialize():
 	_get_agents()
-	_obs_space = agents[0].get_obs_space()
-	_action_space = agents[0].get_action_space()
 	args = _get_args()
-	Engine.physics_ticks_per_second = _get_speedup() * 60 # Replace with function body.
+	Engine.physics_ticks_per_second = _get_speedup() * 60  # Replace with function body.
 	Engine.time_scale = _get_speedup() * 1.0
-	prints("physics ticks", Engine.physics_ticks_per_second, Engine.time_scale, _get_speedup(), speed_up)
-	
-	_set_heuristic("human")
-	match control_mode:
-		ControlModes.TRAINING:
-			connected = connect_to_server()
-			if connected:
-				_set_heuristic("model")
-				_handshake()
-				_send_env_info()  
-			else:
-				push_warning("Couldn't connect to Python server, using human controls instead. ",
-				"Did you start the training server using e.g. `gdrl` from the console?")
-		ControlModes.ONNX_INFERENCE:
-				assert(FileAccess.file_exists(onnx_model_path), "Onnx Model Path set on Sync node does not exist: %s" % onnx_model_path)
-				onnx_model = ONNXModel.new(onnx_model_path, 1)
-				_set_heuristic("model")	
-	
+	prints(
+		"physics ticks",
+		Engine.physics_ticks_per_second,
+		Engine.time_scale,
+		_get_speedup(),
+		speed_up
+	)
+
+	_set_heuristic("human", all_agents)
+
+	_initialize_training_agents()
+	_initialize_inference_agents()
+	_initialize_demo_recording()
+
 	_set_seed()
 	_set_action_repeat()
-	initialized = true  
-
-func _physics_process(_delta): 
+	initialized = true
+
+
+func _initialize_training_agents():
+	if agents_training.size() > 0:
+		_obs_space = agents_training[0].get_obs_space()
+		_action_space = agents_training[0].get_action_space()
+		connected = connect_to_server()
+		if connected:
+			_set_heuristic("model", agents_training)
+			_handshake()
+			_send_env_info()
+		else:
+			push_warning(
+				"Couldn't connect to Python server, using human controls instead. ",
+				"Did you start the training server using e.g. `gdrl` from the console?"
+			)
+
+
+func _initialize_inference_agents():
+	if agents_inference.size() > 0:
+		if control_mode == ControlModes.ONNX_INFERENCE:
+			assert(
+				FileAccess.file_exists(onnx_model_path),
+				"Onnx Model Path set on Sync node does not exist: %s" % onnx_model_path
+			)
+			onnx_models[onnx_model_path] = ONNXModel.new(onnx_model_path, 1)
+
+		for agent in agents_inference:
+			_action_space_inference.append(agent.get_action_space())
+
+			var agent_onnx_model: ONNXModel
+			if agent.onnx_model_path.is_empty():
+				assert(
+					onnx_models.has(onnx_model_path),
+					(
+						"Node %s has no onnx model path set " % agent.get_path()
+						+ "and sync node's control mode is not set to OnnxInference. "
+						+ "Either add the path to the AIController, "
+						+ "or if you want to use the path set on sync node instead, "
+						+ "set control mode to OnnxInference."
+					)
+				)
+				prints(
+					"Info: AIController %s" % agent.get_path(),
+					"has no onnx model path set.",
+					"Using path set on the sync node instead."
+				)
+				agent_onnx_model = onnx_models[onnx_model_path]
+			else:
+				if not onnx_models.has(agent.onnx_model_path):
+					assert(
+						FileAccess.file_exists(agent.onnx_model_path),
+						(
+							"Onnx Model Path set on %s node does not exist: %s"
+							% [agent.get_path(), agent.onnx_model_path]
+						)
+					)
+					onnx_models[agent.onnx_model_path] = ONNXModel.new(agent.onnx_model_path, 1)
+				agent_onnx_model = onnx_models[agent.onnx_model_path]
+
+			agent.onnx_model = agent_onnx_model
+		_set_heuristic("model", agents_inference)
+
+
+func _initialize_demo_recording():
+	if agent_demo_record:
+		InputMap.add_action("RemoveLastDemoEpisode")
+		InputMap.action_add_event(
+			"RemoveLastDemoEpisode", agent_demo_record.remove_last_episode_key
+		)
+		current_demo_trajectory.resize(2)
+		current_demo_trajectory[0] = []
+		current_demo_trajectory[1] = []
+		agent_demo_record.heuristic = "demo_record"
+
+
+func _physics_process(_delta):
 	# two modes, human control, agent control
 	# pause tree, send obs, get actions, set actions, unpause tree
+
+	_demo_record_process()
+
 	if n_action_steps % action_repeat != 0:
 		n_action_steps += 1
 		return
 
 	n_action_steps += 1
-	
+
+	_training_process()
+	_inference_process()
+	_heuristic_process()
+
+
+func _training_process():
 	if connected:
-		get_tree().set_pause(true) 
-		
+		get_tree().set_pause(true)
+
 		if just_reset:
 			just_reset = false
-			var obs = _get_obs_from_agents()
-		
-			var reply = {
-				"type": "reset",
-				"obs": obs
-			}
+			var obs = _get_obs_from_agents(agents_training)
+
+			var reply = {"type": "reset", "obs": obs}
 			_send_dict_as_json_message(reply)
 			# this should go straight to getting the action and setting it checked the agent, no need to perform one phyics tick
-			get_tree().set_pause(false) 
+			get_tree().set_pause(false)
 			return
-		
+
 		if need_to_send_obs:
 			need_to_send_obs = false
 			var reward = _get_reward_from_agents()
 			var done = _get_done_from_agents()
 			#_reset_agents_if_done() # this ensures the new observation is from the next env instance : NEEDS REFACTOR
-			
-			var obs = _get_obs_from_agents()
-			
-			var reply = {
-				"type": "step",
-				"obs": obs,
-				"reward": reward,
-				"done": done
-			}
+
+			var obs = _get_obs_from_agents(agents_training)
+
+			var reply = {"type": "step", "obs": obs, "reward": reward, "done": done}
 			_send_dict_as_json_message(reply)
-		
+
 		var handled = handle_message()
-	
-	elif onnx_model != null:
-		var obs : Array = _get_obs_from_agents()
-	
+
+
+func _inference_process():
+	if agents_inference.size() > 0:
+		var obs: Array = _get_obs_from_agents(agents_inference)
 		var actions = []
-		for o in obs:
-			var action = onnx_model.run_inference(o["obs"], 1.0)
+
+		for agent_id in range(0, agents_inference.size()):
+			var action = agents_inference[agent_id].onnx_model.run_inference(
+				obs[agent_id]["obs"], 1.0
+			)
 			action["output"] = clamp_array(action["output"], -1.0, 1.0)
-			var action_dict = _extract_action_dict(action["output"])
+			var action_dict = _extract_action_dict(
+				action["output"], _action_space_inference[agent_id]
+			)
 			actions.append(action_dict)
-		
-		_set_agent_actions(actions) 
-		need_to_send_obs = true
-		get_tree().set_pause(false) 
-		_reset_agents_if_done()	
-		
+
+		_set_agent_actions(actions, agents_inference)
+		_reset_agents_if_done(agents_inference)
+		get_tree().set_pause(false)
+
+
+func _demo_record_process():
+	if not agent_demo_record:
+		return
+
+	if Input.is_action_just_pressed("RemoveLastDemoEpisode"):
+		print("[Sync script][Demo recorder] Removing last recorded episode.")
+		demo_trajectories.remove_at(demo_trajectories.size() - 1)
+		print("Remaining episode count: %d" % demo_trajectories.size())
+
+	if n_action_steps % agent_demo_record.action_repeat != 0:
+		return
+
+	var obs_dict: Dictionary = agent_demo_record.get_obs()
+
+	# Get the current obs from the agent
+	assert(
+		obs_dict.has("obs"),
+		"Demo recorder needs an 'obs' key in get_obs() returned dictionary to record obs from."
+	)
+	current_demo_trajectory[0].append(obs_dict.obs)
+
+	# Get the action applied for the current obs from the agent
+	agent_demo_record.set_action()
+	var acts = agent_demo_record.get_action()
+
+	var terminal = agent_demo_record.get_done()
+	# Record actions only for non-terminal states
+	if terminal:
+		agent_demo_record.set_done_false()
 	else:
-		_reset_agents_if_done()	
+		current_demo_trajectory[1].append(acts)
+
+	if terminal:
+		#current_demo_trajectory[2].append(true)
+		demo_trajectories.append(current_demo_trajectory.duplicate(true))
+		print("[Sync script][Demo recorder] Recorded episode count: %d" % demo_trajectories.size())
+		current_demo_trajectory[0].clear()
+		current_demo_trajectory[1].clear()
+
 
-func _extract_action_dict(action_array: Array):
+func _heuristic_process():
+	for agent in agents_heuristic:
+		_reset_agents_if_done(agents_heuristic)
+
+
+func _extract_action_dict(action_array: Array, action_space: Dictionary):
 	var index = 0
 	var result = {}
-	for key in _action_space.keys():
-		var size = _action_space[key]["size"]
-		if _action_space[key]["action_type"] == "discrete":
+	for key in action_space.keys():
+		var size = action_space[key]["size"]
+		if action_space[key]["action_type"] == "discrete":
 			result[key] = round(action_array[index])
 		else:
-			result[key] = action_array.slice(index,index+size)
+			result[key] = action_array.slice(index, index + size)
 		index += size
-		
+
 	return result
 
-func _get_agents():
-	agents = get_tree().get_nodes_in_group("AGENT")
 
-func _set_heuristic(heuristic):
+## For AIControllers that inherit mode from sync, sets the correct mode.
+func _set_agent_mode(agent: Node):
+	var agent_inherits_mode: bool = agent.control_mode == agent.ControlModes.INHERIT_FROM_SYNC
+
+	if agent_inherits_mode:
+		match control_mode:
+			ControlModes.HUMAN:
+				agent.control_mode = agent.ControlModes.HUMAN
+			ControlModes.TRAINING:
+				agent.control_mode = agent.ControlModes.TRAINING
+			ControlModes.ONNX_INFERENCE:
+				agent.control_mode = agent.ControlModes.ONNX_INFERENCE
+
+
+func _get_agents():
+	all_agents = get_tree().get_nodes_in_group("AGENT")
+	for agent in all_agents:
+		_set_agent_mode(agent)
+
+		if agent.control_mode == agent.ControlModes.TRAINING:
+			agents_training.append(agent)
+		elif agent.control_mode == agent.ControlModes.ONNX_INFERENCE:
+			agents_inference.append(agent)
+		elif agent.control_mode == agent.ControlModes.HUMAN:
+			agents_heuristic.append(agent)
+		elif agent.control_mode == agent.ControlModes.RECORD_EXPERT_DEMOS:
+			assert(
+				not agent_demo_record,
+				"Currently only a single AIController can be used for recording expert demos."
+			)
+			agent_demo_record = agent
+
+
+func _set_heuristic(heuristic, agents: Array):
 	for agent in agents:
 		agent.set_heuristic(heuristic)
 
+
 func _handshake():
 	print("performing handshake")
-	
+
 	var json_dict = _get_dict_json_message()
 	assert(json_dict["type"] == "handshake")
 	var major_version = json_dict["major_version"]
 	var minor_version = json_dict["minor_version"]
 	if major_version != MAJOR_VERSION:
-		print("WARNING: major verison mismatch ", major_version, " ", MAJOR_VERSION)  
+		print("WARNING: major verison mismatch ", major_version, " ", MAJOR_VERSION)
 	if minor_version != MINOR_VERSION:
 		print("WARNING: minor verison mismatch ", minor_version, " ", MINOR_VERSION)
-		
+
 	print("handshake complete")
 
+
 func _get_dict_json_message():
 	# returns a dictionary from of the most recent message
 	# this is not waiting
@@ -172,45 +341,48 @@ func _get_dict_json_message():
 			return null
 
 		OS.delay_usec(10)
-		
+
 	var message = stream.get_string()
 	var json_data = JSON.parse_string(message)
-	
+
 	return json_data
 
+
 func _send_dict_as_json_message(dict):
-	stream.put_string(JSON.stringify(dict))
+	stream.put_string(JSON.stringify(dict, "", false))
+
 
 func _send_env_info():
 	var json_dict = _get_dict_json_message()
 	assert(json_dict["type"] == "env_info")
 
-		
 	var message = {
-		"type" : "env_info",
+		"type": "env_info",
 		"observation_space": _obs_space,
-		"action_space":_action_space,
-		"n_agents": len(agents)
-		}
+		"action_space": _action_space,
+		"n_agents": len(agents_training)
+	}
 	_send_dict_as_json_message(message)
 
+
 func connect_to_server():
 	print("Waiting for one second to allow server to start")
 	OS.delay_msec(1000)
 	print("trying to connect to server")
 	stream = StreamPeerTCP.new()
-	
+
 	# "localhost" was not working on windows VM, had to use the IP
 	var ip = "127.0.0.1"
 	var port = _get_port()
 	var connect = stream.connect_to_host(ip, port)
-	stream.set_no_delay(true) # TODO check if this improves performance or not
+	stream.set_no_delay(true)  # TODO check if this improves performance or not
 	stream.poll()
 	# Fetch the status until it is either connected (2) or failed to connect (3)
 	while stream.get_status() < 2:
 		stream.poll()
 	return stream.get_status() == 2
 
+
 func _get_args():
 	print("getting command line arguments")
 	var arguments = {}
@@ -224,41 +396,45 @@ func _get_args():
 			# with the value set to an empty string.
 			arguments[argument.lstrip("--")] = ""
 
-	return arguments   
+	return arguments
+
 
 func _get_speedup():
 	print(args)
-	return args.get("speedup", str(speed_up)).to_int()
+	return args.get("speedup", str(speed_up)).to_float()
 
-func _get_port():    
+
+func _get_port():
 	return args.get("port", DEFAULT_PORT).to_int()
 
+
 func _set_seed():
 	var _seed = args.get("env_seed", DEFAULT_SEED).to_int()
 	seed(_seed)
 
+
 func _set_action_repeat():
 	action_repeat = args.get("action_repeat", str(action_repeat)).to_int()
-	
+
+
 func disconnect_from_server():
 	stream.disconnect_from_host()
 
 
-
 func handle_message() -> bool:
 	# get json message: reset, step, close
 	var message = _get_dict_json_message()
 	if message["type"] == "close":
 		print("received close message, closing game")
 		get_tree().quit()
-		get_tree().set_pause(false) 
+		get_tree().set_pause(false)
 		return true
-		
+
 	if message["type"] == "reset":
 		print("resetting all agents")
-		_reset_all_agents()
+		_reset_agents()
 		just_reset = true
-		get_tree().set_pause(false) 
+		get_tree().set_pause(false)
 		#print("resetting forcing draw")
 #        RenderingServer.force_draw()
 #        var obs = _get_obs_from_agents()
@@ -267,76 +443,98 @@ func handle_message() -> bool:
 #            "type": "reset",
 #            "obs": obs
 #        }
-#        _send_dict_as_json_message(reply)   
+#        _send_dict_as_json_message(reply)
 		return true
-		
+
 	if message["type"] == "call":
 		var method = message["method"]
 		var returns = _call_method_on_agents(method)
-		var reply = {
-			"type": "call",
-			"returns": returns
-		}
+		var reply = {"type": "call", "returns": returns}
 		print("calling method from Python")
-		_send_dict_as_json_message(reply)   
+		_send_dict_as_json_message(reply)
 		return handle_message()
-	
+
 	if message["type"] == "action":
 		var action = message["action"]
-		_set_agent_actions(action) 
+		_set_agent_actions(action, agents_training)
 		need_to_send_obs = true
-		get_tree().set_pause(false) 
+		get_tree().set_pause(false)
 		return true
-		
+
 	print("message was not handled")
 	return false
 
+
 func _call_method_on_agents(method):
 	var returns = []
-	for agent in agents:
+	for agent in all_agents:
 		returns.append(agent.call(method))
-		
+
 	return returns
 
 
-func _reset_agents_if_done():
+func _reset_agents_if_done(agents = all_agents):
 	for agent in agents:
-		if agent.get_done(): 
+		if agent.get_done():
 			agent.set_done_false()
 
-func _reset_all_agents():
+
+func _reset_agents(agents = all_agents):
 	for agent in agents:
 		agent.needs_reset = true
-		#agent.reset()   
+		#agent.reset()
 
-func _get_obs_from_agents():
+
+func _get_obs_from_agents(agents: Array = all_agents):
 	var obs = []
 	for agent in agents:
 		obs.append(agent.get_obs())
-
 	return obs
-	
-func _get_reward_from_agents():
-	var rewards = [] 
+
+
+func _get_reward_from_agents(agents: Array = agents_training):
+	var rewards = []
 	for agent in agents:
 		rewards.append(agent.get_reward())
 		agent.zero_reward()
-	return rewards    
-	
-func _get_done_from_agents():
-	var dones = [] 
+	return rewards
+
+
+func _get_done_from_agents(agents: Array = agents_training):
+	var dones = []
 	for agent in agents:
 		var done = agent.get_done()
-		if done: agent.set_done_false()
+		if done:
+			agent.set_done_false()
 		dones.append(done)
-	return dones    
-	
-func _set_agent_actions(actions):
+	return dones
+
+
+func _set_agent_actions(actions, agents: Array = all_agents):
 	for i in range(len(actions)):
 		agents[i].set_action(actions[i])
-	
-func clamp_array(arr : Array, min:float, max:float):
-	var output : Array = []
+
+
+func clamp_array(arr: Array, min: float, max: float):
+	var output: Array = []
 	for a in arr:
 		output.append(clamp(a, min, max))
 	return output
+
+
+## Save recorded export demos on window exit (Close window instead of "Stop" button in Godot Editor)
+func _notification(what):
+	if not agent_demo_record:
+		return
+
+	if what == NOTIFICATION_PREDELETE:
+		var json_string = JSON.stringify(demo_trajectories, "", false)
+		var file = FileAccess.open(agent_demo_record.expert_demo_save_path, FileAccess.WRITE)
+
+		if not file:
+			var error: Error = FileAccess.get_open_error()
+			assert(not error, "There was an error opening the file: %d" % error)
+
+		file.store_line(json_string)
+		var error = file.get_error()
+		assert(not error, "There was an error after trying to write to the file: %d" % error)

bin/Ships.pck

@@ -1,3 +1,3 @@
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-oid sha256:263f8fcb2b07f49d3ea0f8b9e417b39cb07f1f2e93653d1e49f98e9ecf8f4268
-size 3509248
+oid sha256:a3a39e9952bc1408db59615be62aa11cbf535bc1d61f58d5d9e89f6e95fe9807
+size 3584464

bin/data_GridSensor3DExample_linuxbsd_x86_64/GodotSharp.dll

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2f682df7d28190b6cf0e9a4ac452c31cd42473a8b0b1ac05dbc72b914f6a13f3
+size 4559872

bin/data_GridSensor3DExample_linuxbsd_x86_64/GridSensor3DExample.deps.json

@@ -0,0 +1,2980 @@
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+    "signature": ""
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+          "GodotSharp": "4.2.1",
+          "Microsoft.ML.OnnxRuntime": "1.15.1",
+          "runtimepack.Microsoft.NETCore.App.Runtime.linux-x64": "6.0.27"
+        },
+        "runtime": {
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+        }
+      },
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+      "linux-x64",
+      "linux",
+      "unix-x64",
+      "unix",
+      "any",
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+    ],
+    "ubuntu.20.04-x64": [
+      "ubuntu.20.04",
+      "ubuntu-x64",
+      "ubuntu",
+      "debian-x64",
+      "debian",
+      "linux-x64",
+      "linux",
+      "unix-x64",
+      "unix",
+      "any",
+      "base"
+    ],
+    "ubuntu.20.10-x64": [
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+      "ubuntu-x64",
+      "ubuntu",
+      "debian-x64",
+      "debian",
+      "linux-x64",
+      "linux",
+      "unix-x64",
+      "unix",
+      "any",
+      "base"
+    ],
+    "ubuntu.21.04-x64": [
+      "ubuntu.21.04",
+      "ubuntu-x64",
+      "ubuntu",
+      "debian-x64",
+      "debian",
+      "linux-x64",
+      "linux",
+      "unix-x64",
+      "unix",
+      "any",
+      "base"
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+      "ubuntu-x64",
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+      "unix-x64",
+      "unix",
+      "any",
+      "base"
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+      "ubuntu-x64",
+      "ubuntu",
+      "debian-x64",
+      "debian",
+      "linux-x64",
+      "linux",
+      "unix-x64",
+      "unix",
+      "any",
+      "base"
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+      "ubuntu-x64",
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+      "linux",
+      "unix-x64",
+      "unix",
+      "any",
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+      "ubuntu-x64",
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+      "unix-x64",
+      "unix",
+      "any",
+      "base"
+    ]
+  }
+}

bin/data_GridSensor3DExample_linuxbsd_x86_64/GridSensor3DExample.runtimeconfig.json

@@ -0,0 +1,14 @@
+{
+  "runtimeOptions": {
+    "tfm": "net6.0",
+    "includedFrameworks": [
+      {
+        "name": "Microsoft.NETCore.App",
+        "version": "6.0.27"
+      }
+    ],
+    "configProperties": {
+      "System.Reflection.Metadata.MetadataUpdater.IsSupported": false
+    }
+  }
+}

bin/data_GridSensor3DExample_linuxbsd_x86_64/Microsoft.VisualBasic.Core.dll

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:33c091d557a11ea094e060e920708124c5ff5d620294a53683f9f82700d4896a
+size 1232656

bin/data_GridSensor3DExample_linuxbsd_x86_64/System.Data.Common.dll

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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+size 3016992