#2453 - Updating with some explanation to improve the readability of the notebook
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@@ -1,5 +1,16 @@
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"cells": [
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"cells": [
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Training an SB3 Agent\n",
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"\n",
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"This notebook will demonstrate how to use primaite to create and train a PPO agent.\n",
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"\n",
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"#### First, import `PrimaiteGymEnv` and read our config file"
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]
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},
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"cell_type": "code",
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"cell_type": "code",
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"execution_count": null,
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"execution_count": null,
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@@ -69,7 +80,8 @@
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"metadata": {},
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"metadata": {},
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"outputs": [],
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"outputs": [],
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"source": [
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"source": [
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"model.learn(total_timesteps=NO_STEPS)\n"
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"model.learn(total_timesteps=NO_STEPS)\n",
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"model.save(\"PrimAITE-PPO-example-agent\")"
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]
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]
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},
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},
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@@ -78,7 +90,7 @@
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"metadata": {},
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"metadata": {},
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"outputs": [],
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"outputs": [],
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"source": [
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"source": [
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"model.save(\"PrimAITE-v3.0.0b7-PPO\")"
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"model.save(\"PrimAITE-PPO-example-agent\")"
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]
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]
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},
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@@ -88,7 +100,7 @@
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"outputs": [],
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"outputs": [],
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"source": [
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"source": [
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"eval_model = PPO(\"MlpPolicy\", gym)\n",
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"eval_model = PPO(\"MlpPolicy\", gym)\n",
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"eval_model = PPO.load(\"PrimAITE-v3.0.0b7-PPO\", gym)"
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"eval_model = PPO.load(\"PrimAITE-PPO-example-agent\", gym)"
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]
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]
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},
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},
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{
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{
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