20624 lines
1.2 MiB
20624 lines
1.2 MiB
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 34,
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"id": "8104e2db-b1a8-40a0-a238-5d9149fd74b0",
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"metadata": {},
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"outputs": [],
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"source": [
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"from mlagents_envs.environment import UnityEnvironment\n",
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"import mlagents_envs\n",
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"import numpy as np"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 74,
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"id": "6f477382-acc9-4aec-907a-7f58caf955ed",
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"metadata": {},
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"outputs": [],
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"source": [
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"import random"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 83,
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"id": "b7f60f26-0a90-4ea5-b2c2-b5683bda56a6",
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"metadata": {},
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"outputs": [],
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"source": [
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"env = UnityEnvironment()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 84,
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"id": "5929b410-12c3-4bd9-b984-b2c29a76c3f3",
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"metadata": {},
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"outputs": [],
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"source": [
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"env.reset()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 85,
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"id": "f108ff09-9f42-4405-add3-6df941c48f8b",
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"metadata": {
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"scrolled": true,
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"tags": []
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Step\n",
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"(<mlagents_envs.base_env.DecisionSteps object at 0x107ca0af0>, <mlagents_envs.base_env.TerminalSteps object at 0x107ca0250>)\n",
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"DecisionStep(obs=[array([[0., 1., 1., 0., 0.],\n",
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" [0., 1., 1., 0., 0.],\n",
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" [0., 1., 1., 0., 0.],\n",
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" [0., 0., 0., 0., 0.],\n",
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" [0., 0., 0., 0., 0.],\n",
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" [0., 0., 0., 0., 0.],\n",
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" [0., 0., 0., 0., 0.],\n",
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" [0., 0., 0., 0., 0.],\n",
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" [0., 0., 0., 0., 0.],\n",
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" [0., 0., 0., 0., 0.]], dtype=float32), array([ 0. , 0. , 0. , 3. , 3. , 3. ,\n",
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" 0. , 0. , 1. , 1. , 0. , 0. ,\n",
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" 0. , 78.21462], dtype=float32)], reward=0.0, agent_id=0, action_mask=[array([False]), array([False]), array([False])], group_id=0, group_reward=0.0)\n",
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"0.0\n",
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"Step\n",
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"(<mlagents_envs.base_env.DecisionSteps object at 0x1052cafd0>, <mlagents_envs.base_env.TerminalSteps object at 0x1052ca9d0>)\n",
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"DecisionStep(obs=[array([[0., 1., 1., 0., 0.],\n",
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" [0., 1., 1., 0., 0.],\n",
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" 0. , 78.21462], dtype=float32)], reward=0.0, agent_id=0, action_mask=[array([False]), array([False]), array([False])], group_id=0, group_reward=0.0)\n",
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"0.0\n",
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"Step\n",
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"(<mlagents_envs.base_env.DecisionSteps object at 0x107ca0220>, <mlagents_envs.base_env.TerminalSteps object at 0x107ca0af0>)\n",
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"DecisionStep(obs=[array([[0., 1., 1., 0., 0.],\n",
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" 0. , 78.21462], dtype=float32)], reward=0.0, agent_id=0, action_mask=[array([False]), array([False]), array([False])], group_id=0, group_reward=0.0)\n",
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"0.0\n",
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"Step\n",
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"(<mlagents_envs.base_env.DecisionSteps object at 0x107ceb880>, <mlagents_envs.base_env.TerminalSteps object at 0x107ceb070>)\n",
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"DecisionStep(obs=[array([[0., 1., 1., 0., 0.],\n",
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" 0. , 78.21462], dtype=float32)], reward=0.0, agent_id=0, action_mask=[array([False]), array([False]), array([False])], group_id=0, group_reward=0.0)\n",
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"0.0\n",
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"Step\n",
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"(<mlagents_envs.base_env.DecisionSteps object at 0x107ca09a0>, <mlagents_envs.base_env.TerminalSteps object at 0x107ca0eb0>)\n",
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"DecisionStep(obs=[array([[0., 1., 1., 0., 0.],\n",
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" [0., 1., 1., 0., 0.],\n",
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" [0., 0., 0., 0., 0.]], dtype=float32), array([ 0. , 0. , 0. , 3. , 3. , 3. ,\n",
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" 2. , 1. , 2. , 1. , 0. , 0. ,\n",
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" 0. , 78.21462], dtype=float32)], reward=0.0, agent_id=0, action_mask=[array([False]), array([False]), array([False])], group_id=0, group_reward=0.0)\n",
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"0.0\n",
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"Step\n",
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"(<mlagents_envs.base_env.DecisionSteps object at 0x107ceb3d0>, <mlagents_envs.base_env.TerminalSteps object at 0x107ceb5b0>)\n",
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"DecisionStep(obs=[array([[0., 1., 1., 0., 0.],\n",
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" [0., 0., 0., 0., 0.]], dtype=float32), array([ 0. , 0. , 0. , 3. , 3. , 3. ,\n",
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" 1. , 2. , 2. , 1. , 0. , 0. ,\n",
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" 0. , 78.21462], dtype=float32)], reward=0.0, agent_id=0, action_mask=[array([False]), array([False]), array([False])], group_id=0, group_reward=0.0)\n",
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"0.0\n",
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"Step\n",
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"(<mlagents_envs.base_env.DecisionSteps object at 0x107c67370>, <mlagents_envs.base_env.TerminalSteps object at 0x107cebb20>)\n",
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"DecisionStep(obs=[array([[0., 1., 0., 0., 0.],\n",
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" 2. , 1. , 2. , 1. , 0. , 0. ,\n",
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" 0. , 78.21462], dtype=float32)], reward=0.0, agent_id=0, action_mask=[array([False]), array([False]), array([False])], group_id=0, group_reward=0.0)\n",
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"0.0\n",
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"(<mlagents_envs.base_env.DecisionSteps object at 0x107cebc40>, <mlagents_envs.base_env.TerminalSteps object at 0x107cebd30>)\n",
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" 0. , 78.21462], dtype=float32)], reward=0.0, agent_id=0, action_mask=[array([False]), array([False]), array([False])], group_id=0, group_reward=0.0)\n",
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"0.0\n",
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"Step\n",
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"(<mlagents_envs.base_env.DecisionSteps object at 0x107c674c0>, <mlagents_envs.base_env.TerminalSteps object at 0x107ceba00>)\n",
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"DecisionStep(obs=[array([[0., 1., 0., 0., 0.],\n",
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"(<mlagents_envs.base_env.DecisionSteps object at 0x107ca0e80>, <mlagents_envs.base_env.TerminalSteps object at 0x107ca0580>)\n",
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" 0. , 78.21462], dtype=float32)], reward=0.0, agent_id=0, action_mask=[array([False]), array([False]), array([False])], group_id=0, group_reward=0.0)\n",
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"0.0\n",
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"(<mlagents_envs.base_env.DecisionSteps object at 0x107ca01c0>, <mlagents_envs.base_env.TerminalSteps object at 0x107ca0790>)\n",
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" 0. , 78.21462], dtype=float32)], reward=0.0, agent_id=0, action_mask=[array([False]), array([False]), array([False])], group_id=0, group_reward=0.0)\n",
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" 0. , 78.21462], dtype=float32)], reward=0.0, agent_id=0, action_mask=[array([False]), array([False]), array([False])], group_id=0, group_reward=0.0)\n",
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"(<mlagents_envs.base_env.DecisionSteps object at 0x107ca03d0>, <mlagents_envs.base_env.TerminalSteps object at 0x107ca0340>)\n",
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" [0., 0., 0., 0., 0.],\n",
|
|
" [0., 0., 0., 0., 0.],\n",
|
|
" [0., 0., 0., 0., 0.],\n",
|
|
" [0., 0., 0., 0., 0.],\n",
|
|
" [0., 0., 0., 0., 0.],\n",
|
|
" [0., 0., 0., 0., 0.]], dtype=float32), array([ 0. , 0. , 0. , 3. , 3. , 3. ,\n",
|
|
" 0. , 1. , 2. , 1. , 0. , 0. ,\n",
|
|
" 0. , 91.30669], dtype=float32)], reward=0.0, agent_id=0, action_mask=[array([False]), array([False]), array([False])], group_id=0, group_reward=0.0)\n",
|
|
"0.0\n",
|
|
"Step\n",
|
|
"(<mlagents_envs.base_env.DecisionSteps object at 0x107cebd30>, <mlagents_envs.base_env.TerminalSteps object at 0x107ceb3d0>)\n",
|
|
"DecisionStep(obs=[array([[0., 1., 0., 0., 0.],\n",
|
|
" [0., 1., 0., 0., 0.],\n",
|
|
" [0., 1., 1., 0., 0.],\n",
|
|
" [0., 0., 0., 0., 0.],\n",
|
|
" [0., 0., 0., 0., 0.],\n",
|
|
" [0., 0., 0., 0., 0.],\n",
|
|
" [0., 0., 0., 0., 0.],\n",
|
|
" [0., 0., 0., 0., 0.],\n",
|
|
" [0., 0., 0., 0., 0.],\n",
|
|
" [0., 0., 0., 0., 0.]], dtype=float32), array([ 0. , 0. , 0. , 3. , 3. , 3. ,\n",
|
|
" 1. , 1. , 2. , 1. , 0. , 0. ,\n",
|
|
" 0. , 91.30669], dtype=float32)], reward=0.0, agent_id=0, action_mask=[array([False]), array([False]), array([False])], group_id=0, group_reward=0.0)\n",
|
|
"0.0\n",
|
|
"Step\n",
|
|
"(<mlagents_envs.base_env.DecisionSteps object at 0x107cd0580>, <mlagents_envs.base_env.TerminalSteps object at 0x107c67910>)\n",
|
|
"DecisionStep(obs=[array([[0., 1., 1., 0., 0.],\n",
|
|
" [0., 1., 1., 0., 0.],\n",
|
|
" [0., 1., 1., 0., 0.],\n",
|
|
" [0., 0., 0., 0., 0.],\n",
|
|
" [0., 0., 0., 0., 0.],\n",
|
|
" [0., 0., 0., 0., 0.],\n",
|
|
" [0., 0., 0., 0., 0.],\n",
|
|
" [0., 0., 0., 0., 0.],\n",
|
|
" [0., 0., 0., 0., 0.],\n",
|
|
" [0., 0., 0., 0., 0.]], dtype=float32), array([ 0. , 0. , 0. , 3. , 3. , 3. ,\n",
|
|
" 1. , 0. , 2. , 1. , 0. , 0. ,\n",
|
|
" 0. , 91.30669], dtype=float32)], reward=0.0, agent_id=0, action_mask=[array([False]), array([False]), array([False])], group_id=0, group_reward=0.0)\n",
|
|
"0.0\n",
|
|
"Step\n",
|
|
"(<mlagents_envs.base_env.DecisionSteps object at 0x107ceb700>, <mlagents_envs.base_env.TerminalSteps object at 0x107ceb0d0>)\n",
|
|
"DecisionStep(obs=[array([[0., 1., 1., 0., 0.],\n",
|
|
" [0., 1., 1., 0., 0.],\n",
|
|
" [0., 1., 1., 0., 0.],\n",
|
|
" [0., 0., 0., 0., 0.],\n",
|
|
" [0., 0., 0., 0., 0.],\n",
|
|
" [0., 0., 0., 0., 0.],\n",
|
|
" [0., 0., 0., 0., 0.],\n",
|
|
" [0., 0., 0., 0., 0.],\n",
|
|
" [0., 0., 0., 0., 0.],\n",
|
|
" [0., 0., 0., 0., 0.]], dtype=float32), array([ 0. , 0. , 0. , 3. , 3. , 3. ,\n",
|
|
" 0. , 0. , 2. , 1. , 0. , 0. ,\n",
|
|
" 0. , 91.30669], dtype=float32)], reward=0.0, agent_id=0, action_mask=[array([False]), array([False]), array([False])], group_id=0, group_reward=0.0)\n",
|
|
"0.0\n",
|
|
"Step\n",
|
|
"(<mlagents_envs.base_env.DecisionSteps object at 0x107cd0940>, <mlagents_envs.base_env.TerminalSteps object at 0x107cd03d0>)\n",
|
|
"DecisionStep(obs=[array([[0., 1., 0., 0., 0.],\n",
|
|
" [0., 1., 0., 0., 0.],\n",
|
|
" [0., 1., 1., 0., 0.],\n",
|
|
" [0., 0., 0., 0., 0.],\n",
|
|
" [0., 0., 0., 0., 0.],\n",
|
|
" [0., 0., 0., 0., 0.],\n",
|
|
" [0., 0., 0., 0., 0.],\n",
|
|
" [0., 0., 0., 0., 0.],\n",
|
|
" [0., 0., 0., 0., 0.],\n",
|
|
" [0., 0., 0., 0., 0.]], dtype=float32), array([ 0. , 0. , 0. , 3. , 3. , 3. ,\n",
|
|
" 0. , 2. , 2. , 1. , 0. , 0. ,\n",
|
|
" 0. , 91.30669], dtype=float32)], reward=0.0, agent_id=0, action_mask=[array([False]), array([False]), array([False])], group_id=0, group_reward=0.0)\n",
|
|
"0.0\n"
|
|
]
|
|
},
|
|
{
|
|
"ename": "UnityCommunicatorStoppedException",
|
|
"evalue": "Communicator has exited.",
|
|
"output_type": "error",
|
|
"traceback": [
|
|
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
|
"\u001b[0;31mUnityCommunicatorStoppedException\u001b[0m Traceback (most recent call last)",
|
|
"Input \u001b[0;32mIn [85]\u001b[0m, in \u001b[0;36m<cell line: 2>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m:\n\u001b[0;32m----> 2\u001b[0m \u001b[43menv\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstep\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 3\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mStep\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 4\u001b[0m asd \u001b[38;5;241m=\u001b[39m env\u001b[38;5;241m.\u001b[39mget_steps(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mnpc?team=0\u001b[39m\u001b[38;5;124m'\u001b[39m)\n",
|
|
"File \u001b[0;32m~/opt/miniforge3/lib/python3.9/site-packages/mlagents_envs/timers.py:305\u001b[0m, in \u001b[0;36mtimed.<locals>.wrapped\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 303\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mwrapped\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m 304\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m hierarchical_timer(func\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__qualname__\u001b[39m):\n\u001b[0;32m--> 305\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
|
|
"File \u001b[0;32m~/opt/miniforge3/lib/python3.9/site-packages/mlagents_envs/environment.py:350\u001b[0m, in \u001b[0;36mUnityEnvironment.step\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 348\u001b[0m outputs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_communicator\u001b[38;5;241m.\u001b[39mexchange(step_input, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_poll_process)\n\u001b[1;32m 349\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m outputs \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m--> 350\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m UnityCommunicatorStoppedException(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCommunicator has exited.\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 351\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_update_behavior_specs(outputs)\n\u001b[1;32m 352\u001b[0m rl_output \u001b[38;5;241m=\u001b[39m outputs\u001b[38;5;241m.\u001b[39mrl_output\n",
|
|
"\u001b[0;31mUnityCommunicatorStoppedException\u001b[0m: Communicator has exited."
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"while True:\n",
|
|
" env.step()\n",
|
|
" print(\"Step\")\n",
|
|
" asd = env.get_steps('npc?team=0')\n",
|
|
" print(asd)\n",
|
|
" print(asd[0][0])\n",
|
|
" _id = asd[0][0].obs[0][0][0]\n",
|
|
" print(_id)\n",
|
|
" env.set_action_for_agent('npc?team=0', 0, mlagents_envs.environment.ActionTuple(discrete=np.array([[1, 0, random.randint(0,2)]])))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 86,
|
|
"id": "db100c84-22ab-491b-b68d-4d5c1bbc66a3",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"env.close()"
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python 3 (ipykernel)",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.9.12"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 5
|
|
}
|