\n", " | participant_id | \n", "trial_index | \n", "stimulus | \n", "response | \n", "response_time | \n", "expected_response | \n", "is_correct | \n", "
---|---|---|---|---|---|---|---|
0 | \n", "sub-1 | \n", "1 | \n", "A | \n", "None | \n", "NaN | \n", "None | \n", "1 | \n", "
1 | \n", "sub-1 | \n", "2 | \n", "D | \n", "None | \n", "NaN | \n", "None | \n", "1 | \n", "
2 | \n", "sub-1 | \n", "3 | \n", "A | \n", "non-match | \n", "1.697356 | \n", "match | \n", "0 | \n", "
3 | \n", "sub-1 | \n", "4 | \n", "F | \n", "non-match | \n", "0.149110 | \n", "non-match | \n", "1 | \n", "
4 | \n", "sub-1 | \n", "5 | \n", "D | \n", "non-match | \n", "0.277760 | \n", "non-match | \n", "1 | \n", "
Stimuli: {\"\".join(map(str,map(int,stimuli)))}'\n", " f'
Actions: {\"\".join(actions)}'\n", " )\n", "\n", " @staticmethod\n", " def create_environment():\n", " \"\"\"Utility function to create a N-back environment and its spec.\"\"\"\n", "\n", " # Make sure the environment outputs single-precision floats.\n", " environment = wrappers.SinglePrecisionWrapper(NBack())\n", "\n", " # Grab the spec of the environment.\n", " environment_spec = specs.make_environment_spec(environment)\n", "\n", " return environment, environment_spec" ] }, { "cell_type": "markdown", "metadata": { "execution": {} }, "source": [ "### Define a random agent\n", "\n", "For more information you can refer to NMA-DL W3D2 Basic Reinforcement learning." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "execution": {} }, "outputs": [], "source": [ "class RandomAgent(acme.Actor):\n", "\n", " def __init__(self, environment_spec):\n", " \"\"\"Gets the number of available actions from the environment spec.\"\"\"\n", " self._num_actions = environment_spec.actions.num_values\n", "\n", " def select_action(self, observation):\n", " \"\"\"Selects an action uniformly at random.\"\"\"\n", " action = np.random.randint(self._num_actions)\n", " return action\n", "\n", " def observe_first(self, timestep):\n", " \"\"\"Does not record as the RandomAgent has no use for data.\"\"\"\n", " pass\n", "\n", " def observe(self, action, next_timestep):\n", " \"\"\"Does not record as the RandomAgent has no use for data.\"\"\"\n", " pass\n", "\n", " def update(self):\n", " \"\"\"Does not update as the RandomAgent does not learn from data.\"\"\"\n", " pass" ] }, { "cell_type": "markdown", "metadata": { "execution": {} }, "source": [ "### Initialize the environment and the agent" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "execution": {} }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "actions:\n", " DiscreteArray(shape=(), dtype=int32, name=action, minimum=0, maximum=1, num_values=2)\n", "observations:\n", " BoundedArray(shape=(32,), dtype=dtype('float32'), name='nback_stimuli', minimum=0.0, maximum=7.0)\n", "rewards:\n", " Array(shape=(), dtype=dtype('float32'), name='reward')\n" ] } ], "source": [ "env, env_spec = NBack.create_environment()\n", "agent = RandomAgent(env_spec)\n", "\n", "print('actions:\\n', env_spec.actions)\n", "print('observations:\\n', env_spec.observations)\n", "print('rewards:\\n', env_spec.rewards)" ] }, { "cell_type": "markdown", "metadata": { "execution": {} }, "source": [ "### Run the loop" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "execution": {} }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
\n", " | episode_length | \n", "episode_return | \n", "steps_per_second | \n", "episodes | \n", "steps | \n", "
---|---|---|---|---|---|
995 | \n", "32 | \n", "-10.0 | \n", "329.379165 | \n", "996 | \n", "31872 | \n", "
996 | \n", "32 | \n", "-11.0 | \n", "326.324034 | \n", "997 | \n", "31904 | \n", "
997 | \n", "32 | \n", "-9.0 | \n", "373.017676 | \n", "998 | \n", "31936 | \n", "
998 | \n", "32 | \n", "-11.0 | \n", "309.737031 | \n", "999 | \n", "31968 | \n", "
999 | \n", "32 | \n", "-9.0 | \n", "405.329983 | \n", "1000 | \n", "32000 | \n", "