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   "source": [
    "# Broadcast Communication\n",
    "\n",
    "By default, communication occurs between all satellites that are specified by the communication\n",
    "method. This tutorial shows how to use two classes to configure a broadcast action that must be\n",
    "taken for communication to occur:\n",
    "\n",
    "* [Broadcast](../api_reference/act/index.html#bsk_rl.act.Broadcast), which gives satellites an action\n",
    "  that enables communication from them at the end of the current step.\n",
    "* [BroadcastCommunication](../api_reference/comm/index.html#bsk_rl.comm.BroadcastCommunication), which\n",
    "  can be combined with another communication method to limit communication from broadcasters to\n",
    "  those satellites satisfying the requirements of the other communication method.\n",
    "\n",
    "## Configuring the Environment\n",
    "\n",
    "For this example, a multisatellite target imaging environment will be used. The goal is\n",
    "to maximize the value of unique images taken. This configuration is similar to the \n",
    "[Multi-Agent Environments](../examples/multiagent_envs.html) example."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bsk_rl import sats, act, obs, scene, data, comm\n",
    "from bsk_rl.sim import dyn, fsw\n",
    "\n",
    "\n",
    "class ImagingSatellite(sats.ImagingSatellite):\n",
    "    observation_spec = [\n",
    "        obs.OpportunityProperties(\n",
    "            dict(prop=\"priority\"),\n",
    "            dict(prop=\"opportunity_open\", norm=5700.0),\n",
    "            n_ahead_observe=4,\n",
    "        )\n",
    "    ]\n",
    "    action_spec = [act.Broadcast(duration=15.0), act.Image(n_ahead_image=4)]\n",
    "    dyn_type = dyn.FullFeaturedDynModel\n",
    "    fsw_type = fsw.SteeringImagerFSWModel\n",
    "\n",
    "\n",
    "ACTION_BROADCAST = 0\n",
    "ACTION_IMAGE_0 = 1\n",
    "ACTION_IMAGE_1 = 2\n",
    "ACTION_IMAGE_2 = 3\n",
    "ACTION_IMAGE_3 = 4"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Satellite properties are set to give the satellite near-unlimited power and storage resources. To randomize some parameters in a correlated manner across satellites, a ``sat_arg_randomizer`` is set and passed to the environment. In this case, the satellites are distributed in a trivial single-plane Walker-delta constellation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bsk_rl.utils.orbital import walker_delta_args\n",
    "\n",
    "N_AGENTS = 2\n",
    "sat_args = dict(\n",
    "    imageAttErrorRequirement=0.01,\n",
    "    imageRateErrorRequirement=0.01,\n",
    "    batteryStorageCapacity=1e9,\n",
    "    storedCharge_Init=1e9,\n",
    "    dataStorageCapacity=1e12,\n",
    "    u_max=0.4,\n",
    "    K1=0.25,\n",
    "    K3=3.0,\n",
    "    omega_max=0.087,\n",
    "    servo_Ki=5.0,\n",
    "    servo_P=150 / 5,\n",
    ")\n",
    "sat_arg_randomizer = walker_delta_args(\n",
    "    altitude=800.0, inc=60.0, n_planes=1, clustersize=N_AGENTS, clusterspacing=5.0\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A communication type is defined that uses multidegree line-of-sight communication with broadcasting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "class BroadcastLOS(comm.BroadcastCommunication, comm.LOSMultiCommunication):\n",
    "    pass"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, the environment can be instantiated."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bsk_rl import ConstellationTasking\n",
    "\n",
    "env = ConstellationTasking(\n",
    "    satellites=[ImagingSatellite(f\"EO-{i + 1}\", sat_args) for i in range(N_AGENTS)],\n",
    "    scenario=scene.UniformTargets(1000),\n",
    "    rewarder=data.UniqueImageReward(),\n",
    "    communicator=BroadcastLOS(),\n",
    "    sat_arg_randomizer=sat_arg_randomizer,\n",
    "    log_level=\"INFO\",\n",
    ")\n",
    "_ = env.reset()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the first step, both agents are tasked with an imaging action, and one successfully images a target."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "_ = env.step({\"EO-1\": ACTION_IMAGE_3, \"EO-2\": ACTION_IMAGE_2})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When both select the broadcast action, data is shared in both directions. This is subject to line-of-sight availability as well as selecting the correct action."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "_ = env.step({\"EO-1\": ACTION_BROADCAST, \"EO-2\": ACTION_BROADCAST})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "One agent can broadcast while the others are completing a different task."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "_ = env.step({\"EO-1\": ACTION_IMAGE_2, \"EO-2\": ACTION_BROADCAST})  # Agent 1 broadcasts"
   ]
  }
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