diff --git a/overcooked_simulator/game_content/item_info.yaml b/overcooked_simulator/game_content/item_info.yaml
index 1266f61ebd611cd5c2a9097b1be9dd7eff65b7f7..b06b6296f391e37bff755207de3d9029d398f1a0 100644
--- a/overcooked_simulator/game_content/item_info.yaml
+++ b/overcooked_simulator/game_content/item_info.yaml
@@ -70,6 +70,7 @@ Cheese:
Sausage:
type: Ingredient
+# Chopped things
ChoppedTomato:
type: Ingredient
needs: [ Tomato ]
diff --git a/overcooked_simulator/game_content/layouts/rl.layout b/overcooked_simulator/game_content/layouts/rl.layout
index 4b91262e0e78525486821ca6c18edd99097138d8..624af90b4e174a801bfd027e0c9c864450489eef 100644
--- a/overcooked_simulator/game_content/layouts/rl.layout
+++ b/overcooked_simulator/game_content/layouts/rl.layout
@@ -1,4 +1,5 @@
-#X##
-T__#
-U__P
-##W#
+#X###
+T___#
+#___#
+U___P
+##W##
diff --git a/overcooked_simulator/gym_env.py b/overcooked_simulator/gym_env.py
index 26d5da99b0ccdf03e1e17bbf4c278bd9e9ee12c6..2e3f55d7c8cf504d108824beda2e02ac18313310 100644
--- a/overcooked_simulator/gym_env.py
+++ b/overcooked_simulator/gym_env.py
@@ -1,5 +1,6 @@
import json
import time
+from copy import copy, deepcopy
from datetime import timedelta
from enum import Enum
from pathlib import Path
@@ -116,12 +117,25 @@ def get_env_action(player_id, simple_action, duration):
print("FAIL", simple_action)
-environment_config_path: Path = ROOT_DIR / "game_content" / "environment_config_rl.yaml"
-item_info_path: Path = ROOT_DIR / "game_content" / "item_info_rl.yaml"
+
+environment_config_path = ROOT_DIR / "game_content" / "environment_config_rl.yaml"
layout_path: Path = ROOT_DIR / "game_content" / "layouts" / "rl.layout"
+item_info_path = ROOT_DIR / "game_content" / "item_info_rl.yaml"
+with open(item_info_path, "r") as file:
+ item_info = file.read()
+with open(layout_path, "r") as file:
+ layout = file.read()
+with open(environment_config_path, "r") as file:
+ environment_config = file.read()
with open(ROOT_DIR / "gui_2d_vis" / "visualization_rl.yaml", "r") as file:
visualization_config = yaml.safe_load(file)
+vanilla_env: Environment = Environment(
+ env_config=environment_config,
+ layout_config=layout,
+ item_info=item_info,
+ as_files=False
+ )
class EnvGymWrapper(Env):
"""Should enable this:
@@ -135,12 +149,7 @@ class EnvGymWrapper(Env):
self.gridsize = 20
- self.env: Environment = Environment(
- env_config=environment_config_path,
- layout_config=layout_path,
- item_info=item_info_path,
- as_files=True,
- )
+ self.env = deepcopy(vanilla_env)
self.visualizer: Visualizer = Visualizer(config=visualization_config)
self.player_name = str(0)
@@ -160,9 +169,10 @@ class EnvGymWrapper(Env):
self.action_space = spaces.Discrete(len(self.action_space_map))
# Example for using image as input (channel-first; channel-last also works):
- dummy_obs = self.get_env_img(self.gridsize)
+ # dummy_obs = self.get_env_img(self.gridsize)
+ dummy_obs = self.get_vector_state()
self.observation_space = spaces.Box(
- low=0, high=255, shape=dummy_obs.shape, dtype=np.uint8
+ low=0, high=1, shape=dummy_obs.shape, dtype=float
)
self.last_obs = dummy_obs
@@ -182,16 +192,18 @@ class EnvGymWrapper(Env):
timedelta(seconds=self.global_step_time / self.in_between_steps)
)
- observation = self.get_env_img(self.gridsize)
+ # observation = self.get_env_img(self.gridsize)
+ observation = self.get_vector_state()
+
reward = -1
if (
- self.env.order_manager.score > self.prev_score
- and self.env.order_manager.score != 0
+ self.env.score > self.prev_score
+ and self.env.score != 0
):
- self.prev_score = self.env.order_manager.score
+ self.prev_score = self.env.score
reward = 100
- elif self.env.order_manager.score < self.prev_score:
+ elif self.env.score < self.prev_score:
self.prev_score = 0
reward = -1
@@ -203,24 +215,27 @@ class EnvGymWrapper(Env):
return observation, reward, terminated, truncated, info
def reset(self, seed=None, options=None):
- self.env: Environment = Environment(
- env_config=environment_config_path,
- layout_config=layout_path,
- item_info=item_info_path,
- as_files=True,
- )
+ # self.env: Environment = Environment(
+ # env_config=environment_config,
+ # layout_config=layout,
+ # item_info=item_info,
+ # as_files=False
+ # )
+
+ self.env = deepcopy(vanilla_env)
self.player_name = str(0)
self.env.add_player(self.player_name)
self.player_id = list(self.env.players.keys())[0]
-
info = {}
- return self.get_env_img(self.gridsize), info
+ # obs = self.get_env_img(self.gridsize)
+ obs = self.get_vector_state()
+ return obs, info
def render(self):
observation = self.get_env_img(self.gridsize)
img = observation.transpose((1, 2, 0))[:, :, ::-1]
- print(img.shape)
+ # print(img.shape)
img = cv2.resize(img, (img.shape[1] * 5, img.shape[0] * 5))
cv2.imshow("Overcooked", img)
cv2.waitKey(1)
@@ -239,6 +254,8 @@ class EnvGymWrapper(Env):
def get_vector_state(self):
grid, player, env_time, orders = self.env.get_vectorized_state("0")
+ obs = np.concatenate([grid.flatten(), player.flatten()], axis=0)
+ return obs
# flatten: grid + player
# concatenate all (env_time to array)
@@ -248,12 +265,13 @@ class EnvGymWrapper(Env):
# return np.random.randint(len(self.action_space_map))
+
def main():
rl_agent_checkpoints = Path("./rl_agent_checkpoints")
rl_agent_checkpoints.mkdir(exist_ok=True)
config = {
- "policy_type": "CnnPolicy",
+ "policy_type": "MlpPolicy",
"total_timesteps": 1000000, # hendric sagt eher so 300_000_000 schritte
"env_id": "overcooked",
}
@@ -265,7 +283,7 @@ def main():
# # save_code=True, # optional
# )
- env = make_vec_env(EnvGymWrapper, n_envs=4)
+ env = make_vec_env(EnvGymWrapper, n_envs=64)
# env = EnvGymWrapper()
model_classes = [A2C, DQN, PPO]
diff --git a/overcooked_simulator/hooks.py b/overcooked_simulator/hooks.py
index 9d907fcd93f2c4ba6d08cbdbd034c118496ac6c1..fc79f8e31ab90ae2d15f6b2a96bc599fb3c2fae7 100644
--- a/overcooked_simulator/hooks.py
+++ b/overcooked_simulator/hooks.py
@@ -37,6 +37,9 @@ GAME_ENDED_STEP = "game_ended_step"
PRE_STATE = "pre_state"
+PRE_STEP = "pre_step"
+POST_STEP = "post_step"
+
STATE_DICT = "state_dict"
JSON_STATE = "json_state"