relaxed deps

Author: AndreaCensi

README.md

@@ -84,9 +84,9 @@ To do so, first `cd` to the project directory on your local machine. Then, depen
 
 ## Submitting
 
-When the competition opens, you will [submit](https://github.com/duckietown/duckietown-shell#ai-do-submissions) your Docker image using `dt`, the [Duckietown Shell](https://github.com/duckietown/duckietown-shell) like so:
+When the competition opens, you will [submit](https://github.com/duckietown/duckietown-shell#ai-do-submissions) your Docker image using `dts`, the [Duckietown Shell](https://github.com/duckietown/duckietown-shell) like so:
 
-    dt aido18 submit <YOUR_DOCKER_HUB_USERNAME>/<YOUR_IMAGE_BASED_ON_GYM_DUCKIETOWN_AGENT>
+    **** command not ready ****** 
 
 The referenced Docker image will contain a pretrained model which you have trained locally. If you send us a GPU model, we will run it on the simulator only. If you send us an ARM image, we will evaluate the submission and run it on a physical robot, then send you a link to the corresponding log. Should you wish to participate in the robotarium challenge, you must submit an ARM-based image.
 

agent-keyboard-control.py

@@ -1,3 +1,5 @@
+#!/usr/bin/env python
+
 import gym
 import gym_duckietown_agent  # don't remove this line
 import numpy as np
@@ -59,7 +61,7 @@
 
         # We receive the name of the challenge at every time step - just to
         # make sure we are solving the correct task
-        challenge = misc["challenge"]
+        # challenge = misc["challenge"]
 
         stdscr.addstr(2, 0, "action {}".format(action))
         stdscr.addstr(3, 0, "reward {}".format(np.around(rew,3)))
@@ -97,4 +99,4 @@
     np.around(np.mean(rewards), 4),
     np.around(np.max(rewards), 4),
     np.around(np.min(rewards), 4)
-))
+))

gym_duckietown_agent/envs/simplesimagent_env.py

@@ -1,5 +1,4 @@
 import os
-import time
 
 import gym
 from duckietown_slimremote.pc.robot import RemoteRobot

setup.py

@@ -8,7 +8,7 @@
         'gym>=0.9.0',
         'numpy>=1.10.0',
         'duckietown_slimremote>=2018.8.3',
-        'matplotlib==2.2.3',
+        'matplotlib',
         'tqdm>=4.0.0'
     ]
 )