Add initial Vizdoom environment

examples/basic.cfg

@@ -0,0 +1,38 @@
+# Lines starting with # are treated as comments (or with whitespaces+#).
+# It doesn't matter if you use capital letters or not.
+# It doesn't matter if you use underscore or camel notation for keys, e.g. episode_timeout is the same as episodeTimeout.
+
+doom_map = map01
+
+# Rewards
+living_reward = -1
+
+# Rendering options
+screen_resolution = RES_320X240
+screen_format = CRCGCB
+render_hud = True
+render_crosshair = false
+render_weapon = true
+render_decals = false
+render_particles = false
+window_visible = true
+
+# make episodes start after 20 tics (after unholstering the gun)
+episode_start_time = 14
+
+# make episodes finish after 300 actions (tics)
+episode_timeout = 300
+
+# Available buttons
+available_buttons =
+	{
+		MOVE_LEFT
+		MOVE_RIGHT
+		ATTACK
+	}
+
+# Game variables that will be in the state
+available_game_variables = { AMMO2}
+
+mode = PLAYER
+doom_skill = 5

examples/random_agent_example.py

@@ -0,0 +1,25 @@
+from rlkit.agents import RandomAgent
+from rlkit.environments.gym_environment import GymEnvironment
+from rlkit.environments.vizdoom_environment import VizDoomEnvironment
+from rlkit.trainers import BasicTrainer
+
+params = {
+    "environment_params": {
+        # "env_name": "SpaceInvaders-v0",
+    },
+    "agent_params": {
+
+    },
+    "training_params": {
+        "run_name": "test_run",
+        "train_interval": 10,
+        "episodes": 5,
+        "steps": 500,
+    },
+}
+
+# env = GymEnvironment(params["environment_params"])
+env = VizDoomEnvironment(params["environment_params"])
+agent = RandomAgent(params["agent_params"], env.get_action_space())
+trainer = BasicTrainer(params["training_params"], agent, env)
+trainer.train()

rlkit/core/__init__.py

@@ -1,3 +1,4 @@
+from .base_action_space import BaseActionSpace
 from .base_agent import BaseAgent
 from .base_environment import BaseEnvironment
 from .base_trainer import BaseTrainer

rlkit/core/base_action_space.py

@@ -0,0 +1,6 @@
+class BaseActionSpace:
+    def __init__(self):
+        pass
+
+    def sample(self):
+        pass

rlkit/core/base_environment.py

@@ -1,8 +1,12 @@
 class BaseEnvironment:
     def __init__(self):
         self.to_render = False
+        self.done = False
         self.reset()
 
+    def close(self):
+        pass
+
     def execute_action(self, action):
         pass
 
@@ -14,3 +18,6 @@ def render(self):
 
     def setRender(self, to_render):
         self.to_render = to_render
+
+    def get_action_space(self):
+        pass

rlkit/environments/vizdoom_environment.py

@@ -1,14 +1,64 @@
-from rlkit.core import BaseEnvironment
+import random
+import time
+
+from rlkit.core import BaseEnvironment, BaseActionSpace
 from vizdoom import *
 
 class VizDoomEnvironment(BaseEnvironment):
+
+    class VizDoomActionSpace(BaseActionSpace):
+        def __init__(self):
+            self.actions = [
+                # http://www.cs.put.poznan.pl/visualdoomai/tutorial.html
+                [0, 0, 1], # shoot
+                [1, 0, 0], # left
+                [0, 1, 0], # right
+            ]
+            super(VizDoomEnvironment.VizDoomActionSpace, self).__init__()
+
+        def sample(self):
+            return random.sample(self.actions, 1)[0]
+
     def __init__(self, params):
+        self.action_space = self.VizDoomActionSpace()
+        self.initialize_env()
         super(VizDoomEnvironment, self).__init__()
-        self.env_name = params["env_name"]
-
-        pass
 
     def initialize_env(self):
         self.env = DoomGame()
-        self.env.load_config("../config/basic.cfg")
-        self.env.init()
+        self.env.load_config("./basic.cfg") # TODO: load via params
+        self.env.init()
+
+    def get_action_space(self):
+        return self.action_space
+
+    def reset(self, reset_values=True):
+        if reset_values:
+            self.reset_values()
+        self.reset_env()
+
+    def reset_values(self):
+        self.state = None
+        self.reward = None
+        self.done = False
+        self.info = None
+
+    def reset_env(self):
+        self.env.new_episode()
+
+    def step(self, action):
+        self.reward = self.env.make_action(action)
+
+        # TODO: see if need to get image buffer
+        # TODO: see if this happens before/after reward
+        self.state = self.env.get_state()
+
+        self.done = self.env.is_episode_finished()
+        if not self.done:
+            self.info = self.state.game_variables
+        else:
+            self.info = None
+
+        print(action, self.done, self.env.get_total_reward(), self.info)
+        time.sleep(0.02) # TODO: remove
+        return (self.state, self.reward, self.done, self.info, )

rlkit/trainers/basic_trainer.py

@@ -15,7 +15,7 @@ def __init__(self, params, agent, environment):
     def do_step(self):
         action = self.agent.get_action(self.environment.state)
         self.environment.step(action)
-        self.environment.render() # TODO: find better solution
+        # self.environment.render() # TODO: find better solution
 
     def train(self):
         try: