diff --git a/Biped_AlexKumar.pdf b/Biped_AlexKumar.pdf
new file mode 100644
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Binary files /dev/null and b/Biped_AlexKumar.pdf differ
diff --git a/README.md b/README.md
index b65b8d74..9ab0e543 100644
--- a/README.md
+++ b/README.md
@@ -1,3 +1,52 @@
+# Biped Branch
+
+## About this repository
+
+This is the readme for the biped branch of OmniIsaacGymEnvs. To replicate the work, convert the biped URDF to a USD using the built in URDF converter. Make sure to make it instanceable (so it can run parallel efficiently) and remove the fixed base link (so it can walk and doesn't float in the air).
+
+[To view the report for this project](https://github.com/ACK101101/OmniIsaacGymEnvs/blob/biped/Biped_AlexKumar.pdf)
+
+## Important files
+Experiment Runner Bash Script: ./omniisaacgymenvs/auto_runner.sh
+
+Analyze Experiment Python Notebook: ./analysis.ipynb
+
+**Plots Directory:** ./plots/
+Folder for storing tensor plots (from tensorboard information), reward plots (including component-wise breakdowns of the reward function), and metrics plots (for comparing performance across experiments)
+
+**Utils:** ./omniisaacgymenvs/utils/task_util.py; ./omniisaacgymenvs/utils/config_utils/sim_config.py
+
+Added Biped to task_map, maps task name to environment
+
+**Configs:** ./omniisaacgymenvs/cfg/task/Biped.yaml; ./omniisaacgymenvs/cfg/train/BipedPPO.yaml
+
+Set up environment, simulation, and experiment variables (reward strengths, etc)
+
+Added speedWeight, terminationHeading, terminationUp, progress_reward
+
+--
+
+Set up learning variables (learning rate, epochs, etc)
+
+Experimented with lower minibatch_size and number of environments, resolved to defaults after subpar performance
+
+**Articulations:** ./omniisaacgymenvs/robots/articulations/biped.py
+
+Loads in the USD model
+
+**Tasks:** ./omniisaacgymenvs/tasks/base/rl_task.py; ./omniisaacgymenvs/tasks/biped.py; ./omniisaacgymenvs/tasks/shared/locomotion.py
+
+Added logger to save reward components to a text file during training
+
+--
+
+Set up crucial functions to be used when training, such as initializing the environment using the config, populating it with the robot models, resetting a particular environment when conditions are met, and getting joint information
+
+--
+
+Perhaps the most important file. Gets information to compile the reward buffer, uses observations and config variables to compute the reward buffer. Added steps for sending reward information to be logged for post-experiment analysis. Added extra reset conditions and their corresponding death costs, added speed reward and progress word, modified alive reward to alive/dead reward to be more interpretable
+
+---
 # Omniverse Isaac Gym Reinforcement Learning Environments for Isaac Sim
 
 ## About this repository
diff --git a/analysis.ipynb b/analysis.ipynb
new file mode 100644
index 00000000..1dc4ee04
--- /dev/null
+++ b/analysis.ipynb
@@ -0,0 +1,354 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import pandas as pd\n",
+    "from tensorboard.backend.event_processing import event_accumulator\n",
+    "import glob"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# basic params\n",
+    "alive_reward_scale = 2.0\n",
+    "progress_reward = 5.0\n",
+    "deathCost = -5.0\n",
+    "\n",
+    "experiments = [f\"Biped_final_{i}\" for i in range(8)]\n",
+    "alive_reward_scales = 5.0\n",
+    "progress_rewards = [1.0, 1.0, 1.0, 1.0, 5.0, 5.0, 5.0, 5.0]\n",
+    "deathCosts = [-1.0, -1.0, -5.0, -5.0, -5.0, -5.0, -5.0, -5.0]\n",
+    "\n",
+    "experiment = \"Biped_final_7\"\n",
+    "directory = f\"omniisaacgymenvs/runs/{experiment}/\"\n",
+    "isSpeed = True\n",
+    "log_file = directory + f\"{experiment}.txt\"\n",
+    "tensor_file = directory + f\"summaries/*.alex-Blade\"\n",
+    "tensor_file = glob.glob(tensor_file)[-1]\n",
+    "col_names = [\"Ave Reward\", \"Progress Reward\", \"Alive Reward\",\n",
+    "              \"Up Reward\", \"Heading Reward\", \"Action Cost\",\n",
+    "              \"Energy Cost\", \"DOF Limit Cost\"]\n",
+    "if isSpeed: col_names = col_names + [\"Speed Reward\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# parse log and make pd df\n",
+    "def get_parse_log(experiment):\n",
+    "    directory = f\"omniisaacgymenvs/runs/{experiment}/\"\n",
+    "    log_file = directory + f\"{experiment}.txt\"\n",
+    "\n",
+    "    df = []\n",
+    "    with open(log_file, 'r') as f:\n",
+    "        row = []\n",
+    "        for line in f:\n",
+    "            split = line.split(\":\")\n",
+    "            rew_type, val = split[0], split[1].strip()\n",
+    "            \n",
+    "            if rew_type[:4] != \"Step\":\n",
+    "                row.append(float(val))\n",
+    "            else:\n",
+    "                df.append(row)\n",
+    "                row = []\n",
+    "\n",
+    "    df = pd.DataFrame(df[1:][:])\n",
+    "    df.columns = col_names\n",
+    "    df = df.reset_index()\n",
+    "    return df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dfs = []\n",
+    "for x in experiments:\n",
+    "    x_df = get_parse_log(x)\n",
+    "    dfs.append(x_df)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0      0.000000\n",
+       "1     -0.013593\n",
+       "2     -0.021994\n",
+       "3     -0.012777\n",
+       "4     -0.006450\n",
+       "         ...   \n",
+       "635    0.000000\n",
+       "636   -0.001258\n",
+       "637   -0.002370\n",
+       "638    0.000000\n",
+       "639    0.000000\n",
+       "Name: Alive Reward, Length: 640, dtype: float64"
+      ]
+     },
+     "execution_count": 51,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dfs[1]['Alive Reward']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1500x600 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# plot\n",
+    "# Create a bar chart for stacked categories\n",
+    "df = get_parse_log(experiment = \"Biped_final_7\")\n",
+    "fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(15, 6))\n",
+    "\n",
+    "# set cols\n",
+    "line_cols = ['Ave Reward', 'index']\n",
+    "reward_cols = [\"Progress Reward\", \"Alive Reward\",\n",
+    "              \"Up Reward\", \"Heading Reward\"]\n",
+    "if isSpeed: reward_cols = reward_cols + [\"Speed Reward\"]\n",
+    "cost_cols = [\"Action Cost\", \"Energy Cost\", \"DOF Limit Cost\"]\n",
+    "reward_cols.append('index')\n",
+    "cost_cols.append('index')\n",
+    "\n",
+    "df[reward_cols].plot(x='index', kind='line', stacked=False, ax=ax1)\n",
+    "ax1.set_xlabel('Episode Num * 100')\n",
+    "ax1.tick_params(axis='x', labelsize=5)\n",
+    "ax1.set_ylabel('Reward Components')\n",
+    "ax1.legend(loc='center left', bbox_to_anchor=(1, 0.5))\n",
+    "ax1.set_title('Rewards')\n",
+    "\n",
+    "df[cost_cols].plot(x='index', kind='line', stacked=False, ax=ax2)\n",
+    "ax2.set_xlabel('Episode Num * 100')\n",
+    "ax2.tick_params(axis='x', labelsize=5)\n",
+    "ax2.set_ylabel('Cost Components')\n",
+    "ax2.legend(loc='center left', bbox_to_anchor=(1, 0.5))\n",
+    "ax2.set_title('Costs')\n",
+    "\n",
+    "# Create a line plot for 'Ave Reward'\n",
+    "df[line_cols].plot(x='index', kind='line', color='black', marker='o', ax=ax3, markersize=1)\n",
+    "ax3.set_xlabel('Episode Num * 100')\n",
+    "ax3.set_ylabel('Ave Reward')\n",
+    "ax3.set_title('Summed Reward Function')\n",
+    "\n",
+    "plt.tight_layout()\n",
+    "plt.savefig(f\"plots/{experiment}_reward.png\")\n",
+    "plt.show()\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# (total_reward / deathCost)\n",
+    "\n",
+    "# plot\n",
+    "# Create a bar chart for absolute comparison\n",
+    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(15, 6))\n",
+    "\n",
+    "# set cols\n",
+    "prog_plt = ['Progress Reward', 'index']\n",
+    "alive_plt = ['Alive Reward', 'index']\n",
+    "\n",
+    "(df[prog_plt]/progress_reward).plot(x='index', kind='line', stacked=False, ax=ax1)\n",
+    "ax1.set_xlabel('Episode Num * 100')\n",
+    "ax1.tick_params(axis='x', labelsize=5)\n",
+    "ax1.set_ylabel('Progress Made')\n",
+    "ax1.legend(loc='center left', bbox_to_anchor=(1, 0.5))\n",
+    "ax1.set_title('Progress')\n",
+    "\n",
+    "(df[alive_plt]/deathCost).plot(x='index', kind='line', stacked=False, ax=ax2)\n",
+    "ax2.set_xlabel('Episode Num * 100')\n",
+    "ax2.tick_params(axis='x', labelsize=5)\n",
+    "ax2.set_ylabel('Duration Alive')\n",
+    "ax2.legend(loc='center left', bbox_to_anchor=(1, 0.5))\n",
+    "ax2.set_title('Alive')\n",
+    "\n",
+    "plt.tight_layout()\n",
+    "plt.savefig(f\"plots/{experiment}_metrics.png\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# plot\n",
+    "# Create a bar chart for absolute comparison\n",
+    "def comparison_plots(dfs, progress_rewards, deathCosts):\n",
+    "    fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(15, 6))\\\n",
+    "    # set cols\n",
+    "    prog_plt = ['Progress Reward', 'index']\n",
+    "    alive_plt = ['Alive Reward', 'index']\n",
+    "\n",
+    "    experiments = [f\"Biped_{i}\" for i in range(8)]\n",
+    "    for i, df in enumerate(dfs):\n",
+    "        progress_reward = progress_rewards[i]\n",
+    "        deathCost = deathCosts[i]\n",
+    "\n",
+    "        prog = df[prog_plt]\n",
+    "        alive = df[alive_plt]\n",
+    "        prog = prog['Progress Reward'] / progress_reward\n",
+    "        alive = alive['Alive Reward'] / deathCost\n",
+    "\n",
+    "        prog.plot(x='index', kind='line', \n",
+    "                  stacked=False, ax=ax1,\n",
+    "                  linewidth=1, alpha=0.75)\n",
+    "        alive.plot(x='index', kind='line', \n",
+    "                   stacked=False, ax=ax2,\n",
+    "                   linewidth=1, alpha=0.75)\n",
+    "        \n",
+    "    ax1.set_xlabel('Episode Num * 100')\n",
+    "    ax1.tick_params(axis='x', labelsize=5)\n",
+    "    ax1.set_ylabel('Progress Made')\n",
+    "    ax1.legend(experiments, loc='center left', bbox_to_anchor=(1, 0.5))\n",
+    "    ax1.set_title('Progress')\n",
+    "\n",
+    "    ax2.set_xlabel('Episode Num * 100')\n",
+    "    ax2.tick_params(axis='x', labelsize=5)\n",
+    "    ax2.set_ylabel('Death Cost')\n",
+    "    ax2.legend(experiments, loc='center left', bbox_to_anchor=(1, 0.5))\n",
+    "    ax2.set_title('Death')\n",
+    "\n",
+    "    plt.tight_layout()\n",
+    "    plt.savefig(f\"plots/compare_metrics.png\")\n",
+    "    plt.show()\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1500x600 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "comparison_plots(dfs, progress_rewards, deathCosts)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<tensorboard.backend.event_processing.event_accumulator.EventAccumulator at 0x7f6a4b2d5d00>"
+      ]
+     },
+     "execution_count": 63,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "event_acc = event_accumulator.EventAccumulator(tensor_file)\n",
+    "event_acc.Reload()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 2400x600 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# scalar_tags = event_acc.Tags()['scalars']\n",
+    "scalar_tags = ['losses/a_loss', 'losses/c_loss', 'rewards/iter', 'episode_lengths/iter']\n",
+    "scalar_data = {tag: event_acc.Scalars(tag) for tag in scalar_tags}\n",
+    "\n",
+    "fig, axs = plt.subplots(1, 4, figsize=(24, 6))\n",
+    "for i, (tag, data) in enumerate(scalar_data.items()):\n",
+    "    steps = [entry.step for entry in data]\n",
+    "    values = [entry.value for entry in data]\n",
+    "    ax = axs[i]\n",
+    "    ax.plot(steps, values, label=tag, linewidth=1)\n",
+    "    ax.set_title(tag)\n",
+    "    ax.set_xlabel('iter')\n",
+    "    ax.set_ylabel('value')\n",
+    "plt.savefig(f\"plots/{experiment}_tensor.png\")\n",
+    "plt.show()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "661",
+   "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": "3.8.18"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/analysis.py b/analysis.py
new file mode 100644
index 00000000..8c076115
--- /dev/null
+++ b/analysis.py
@@ -0,0 +1,51 @@
+import matplotlib.pyplot as plt
+import pandas as pd
+
+# basic params
+experiment = "Biped_08"
+file = f"omniisaacgym_envs/runs/{experiment}/{experiment}.txt"
+col_names = ["Ave Reward", "Progress Reward", "Alive Reward",
+              "Up Reward", "Heading Reward", "Action Cost",
+              "Energy Cost", "DOF Limit Cost"]
+
+# parse log and make pd df
+df = []
+with open(file, 'r') as f:
+    row = []
+    for line in f:
+        split = line.split(":")
+        rew_type, val = split[0], split[1].strip()
+        
+        if rew_type[:4] != "Step":
+            row.append(float(val))
+        else:
+            df.append(row)
+            row = []
+
+df = pd.DataFrame(df[1:][:])
+df.columns = col_names
+df = df.reset_index()
+
+# plot
+# Create a bar chart for stacked categories
+fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(15, 6))
+# fig, ax1 = plt.subplots(figsize=(10, 6))
+stacked_cols = col_names[1:]
+stacked_cols.append('index')
+line_cols = ['Ave Reward', 'index']
+
+df[stacked_cols].plot(x='index', kind='bar', stacked=True, ax=ax1)
+ax1.set_xlabel('Episode Num * 100')
+ax1.tick_params(axis='x', labelsize=5)
+ax1.set_ylabel('Reward Components')
+ax1.legend(loc='center left', bbox_to_anchor=(1, 0.5))
+
+# Create a line plot for 'Ave Reward'
+df[line_cols].plot(x='index', kind='line', color='black', marker='o', ax=ax2)
+ax2.set_xlabel('Episode Num * 100')
+ax2.set_ylabel('Ave Reward')
+
+plt.tight_layout()
+plt.savefig(f"{experiment}.png")
+plt.show()
+
diff --git a/omniisaacgymenvs/auto_runner.sh b/omniisaacgymenvs/auto_runner.sh
new file mode 100755
index 00000000..c2335663
--- /dev/null
+++ b/omniisaacgymenvs/auto_runner.sh
@@ -0,0 +1,23 @@
+#!/bin/bash
+
+export PYTHON_PATH=~/.local/share/ov/pkg/isaac_sim-2023.1.0/python.sh
+
+$PYTHON_PATH  scripts/rlgames_train.py task=Biped experiment=Biped_final_0 max_iterations=2000 headless=True task.env.deathCost=-1.0 task.env.terminationHeight=0.0 task.env.terminationHeading=0.0 task.env.terminationUp=0.0 task.env.progress_reward=1.0 train.params.config.learning_rate=5e-4
+$PYTHON_PATH  scripts/rlgames_train.py task=Biped experiment=Biped_final_1 max_iterations=2000 headless=True task.env.deathCost=-1.0 task.env.terminationHeight=0.0 task.env.terminationHeading=0.0 task.env.terminationUp=0.0 task.env.progress_reward=1.0 train.params.config.learning_rate=5e-5
+$PYTHON_PATH  scripts/rlgames_train.py task=Biped experiment=Biped_final_2 max_iterations=2000 headless=True task.env.deathCost=-5.0 task.env.terminationHeight=0.0 task.env.terminationHeading=0.0 task.env.terminationUp=0.0 task.env.progress_reward=1.0 train.params.config.learning_rate=5e-5
+$PYTHON_PATH  scripts/rlgames_train.py task=Biped experiment=Biped_final_3 max_iterations=2000 headless=True task.env.deathCost=-5.0 task.env.terminationHeight=0.7 task.env.terminationHeading=0.0 task.env.terminationUp=0.0 task.env.progress_reward=1.0 train.params.config.learning_rate=5e-5
+$PYTHON_PATH  scripts/rlgames_train.py task=Biped experiment=Biped_final_4 max_iterations=2000 headless=True task.env.deathCost=-5.0 task.env.terminationHeight=0.7 task.env.terminationHeading=0.0 task.env.terminationUp=0.0 task.env.progress_reward=5.0 train.params.config.learning_rate=5e-5
+$PYTHON_PATH  scripts/rlgames_train.py task=Biped experiment=Biped_final_5 max_iterations=2000 headless=True task.env.deathCost=-5.0 task.env.terminationHeight=0.7 task.env.terminationHeading=0.0 task.env.terminationUp=0.7 task.env.progress_reward=5.0 train.params.config.learning_rate=5e-5
+$PYTHON_PATH  scripts/rlgames_train.py task=Biped experiment=Biped_final_6 max_iterations=2000 headless=True task.env.deathCost=-5.0 task.env.terminationHeight=0.7 task.env.terminationHeading=0.5 task.env.terminationUp=0.7 task.env.progress_reward=5.0 train.params.config.learning_rate=5e-5
+$PYTHON_PATH  scripts/rlgames_train.py task=Biped experiment=Biped_final_7 max_iterations=2000 headless=True task.env.deathCost=-5.0 task.env.terminationHeight=0.7 task.env.terminationHeading=0.5 task.env.terminationUp=0.7 task.env.progress_reward=5.0 train.params.config.learning_rate=5e-5 task.env.actionsCost=0.03 task.env.energyCost=0.1
+
+# run without resets
+# run with lower lr
+# run with higher death cost
+# run with height reset
+# increase progress reward
+# run with up reset
+# run with heading reset
+# run with higher action and energy cost
+
+# $PYTHON_PATH scripts/rlgames_train.py task=Biped test=True checkpoint=runs/Biped_15_4/nn/Biped_15_4.pth num_envs=2
\ No newline at end of file
diff --git a/omniisaacgymenvs/cfg/task/Biped.yaml b/omniisaacgymenvs/cfg/task/Biped.yaml
new file mode 100644
index 00000000..81d0db6b
--- /dev/null
+++ b/omniisaacgymenvs/cfg/task/Biped.yaml
@@ -0,0 +1,94 @@
+# used to create the object
+name: Biped
+
+physics_engine: ${..physics_engine}
+
+# if given, will override the device setting in gym.
+env: 
+#  numEnvs: ${...num_envs}
+  numEnvs: ${resolve_default:4096,${...num_envs}}
+  envSpacing: 5
+  episodeLength: 1000 
+  enableDebugVis: False
+
+  clipActions: 1.0
+
+  powerScale: 1.0
+  controlFrequencyInv: 2 # 60 Hz
+
+  # reward parameters
+  headingWeight: 0.75  # direction? changed from 0.75
+  upWeight: 0.1       # changed from 0.1
+  speedWeight: 3.0
+
+  # cost parameters
+  actionsCost: 0.01
+  energyCost: 0.05
+  dofVelocityScale: 0.1
+  angularVelocityScale: 0.25
+  contactForceScale: 0.01
+  jointsAtLimitCost: 0.25   # changed from 0.25
+  deathCost: -5.0          # changed from -1.0
+  terminationHeight: 0.7    # changed!
+  terminationHeading: 0.5   # added
+  terminationUp: 0.7        # added
+  alive_reward_scale: 2.0   # changed from 2.0
+  progress_reward: 5.0     # added
+
+sim:
+  dt: 0.0083 # 1/120 s
+  use_gpu_pipeline: ${eq:${...pipeline},"gpu"}
+  gravity: [0.0, 0.0, -9.81]
+  add_ground_plane: True
+  add_distant_light: False
+  use_fabric: True
+  enable_scene_query_support: False
+  disable_contact_processing: False
+
+  # set to True if you use camera sensors in the environment
+  enable_cameras: False
+
+  default_physics_material:
+    static_friction: 1.0
+    dynamic_friction: 1.0
+    restitution: 0.0
+
+  physx:
+    worker_thread_count: ${....num_threads}
+    solver_type: ${....solver_type}
+    use_gpu: ${eq:${....sim_device},"gpu"} # set to False to run on CPU
+    solver_position_iteration_count: 4
+    solver_velocity_iteration_count: 0
+    bounce_threshold_velocity: 0.2
+    friction_offset_threshold: 0.04
+    friction_correlation_distance: 0.025
+    enable_sleeping: True
+    enable_stabilization: True
+    max_depenetration_velocity: 10.0
+
+    # GPU buffers
+    gpu_max_rigid_contact_count: 524288
+    gpu_max_rigid_patch_count: 81920
+    gpu_found_lost_pairs_capacity: 8192
+    gpu_found_lost_aggregate_pairs_capacity: 262144
+    gpu_total_aggregate_pairs_capacity: 8192
+    gpu_max_soft_body_contacts: 1048576
+    gpu_max_particle_contacts: 1048576
+    gpu_heap_capacity: 67108864
+    gpu_temp_buffer_capacity: 16777216
+    gpu_max_num_partitions: 8
+
+  Biped:
+    # -1 to use default values
+    override_usd_defaults: False
+    enable_self_collisions: True
+    enable_gyroscopic_forces: True
+    # also in stage params
+    # per-actor
+    solver_position_iteration_count: 4
+    solver_velocity_iteration_count: 0
+    sleep_threshold: 0.005
+    stabilization_threshold: 0.001
+    # per-body
+    density: -1
+    max_depenetration_velocity: 10.0
diff --git a/omniisaacgymenvs/cfg/task/BipedSAC.yaml b/omniisaacgymenvs/cfg/task/BipedSAC.yaml
new file mode 100644
index 00000000..8b5f2606
--- /dev/null
+++ b/omniisaacgymenvs/cfg/task/BipedSAC.yaml
@@ -0,0 +1,8 @@
+# used to create the object
+defaults:
+  - Biped
+  - _self_
+
+# if given, will override the device setting in gym.
+env:
+  numEnvs: ${resolve_default:64,${...num_envs}}
\ No newline at end of file
diff --git a/omniisaacgymenvs/cfg/task/MyCartpole.yaml b/omniisaacgymenvs/cfg/task/MyCartpole.yaml
new file mode 100644
index 00000000..3b0ad8d1
--- /dev/null
+++ b/omniisaacgymenvs/cfg/task/MyCartpole.yaml
@@ -0,0 +1,105 @@
+# name of the task - this should match the name used in the task mapping dictionary in task_util.py
+name: MyCartpole
+
+# physics engine - only physx is currently supported. This value does not need to be modified.
+physics_engine: ${..physics_engine}
+
+# task-related parameters
+env:
+  # number of environments to create
+  numEnvs: ${resolve_default:512,${...num_envs}}
+  # spacing between each environment (in meters)
+  envSpacing: 4.0
+
+  # Cartpole reset distance limit
+  resetDist: 3.0
+  # Cartpole effort scaling
+  maxEffort: 400.0
+
+  # clip values in observation buffer to be within this range (-5.0 to +5.0)
+  clipObservations: 5.0
+  # clip values in actions to be within this range (-1.0 to +1.0)
+  clipActions: 1.0
+  # perform 2 simulation steps for every action (applies actions every 2 simulation steps)
+  controlFrequencyInv: 2 # 60 Hz
+
+# simulation related parameters
+sim:
+  # simulation dt (dt between each simulation step)
+  dt: 0.0083 # 1/120 s
+  # whether to use the GPU pipeline - data returned from Isaac Sim APIs will be on the GPU if set to True
+  use_gpu_pipeline: ${eq:${...pipeline},"gpu"}
+  # gravity vector for the simulation scene
+  gravity: [0.0, 0.0, -9.81]
+
+  # whether to add a ground plane to the world
+  add_ground_plane: True
+  # whether to add lighting to the world
+  add_distant_light: False
+
+  # enable flatcache - this is required for rendering
+  use_flatcache: True
+  # disable scene query - this will disable interaction with the scene to improve performance
+  # this must be set to True for ray casting
+  enable_scene_query_support: False
+  # disable additional contact processing to improve performance. This should be set to True when using RigidContactView
+  disable_contact_processing: False
+
+  # set to True if you use camera sensors in the environment
+  enable_cameras: False
+
+  # default parameters if no additional physics materials are specified
+  default_physics_material:
+    static_friction: 1.0
+    dynamic_friction: 1.0
+    restitution: 0.0
+
+  # PhysX related parameters
+  # Additional USD physics schema documentation can be found here: https://docs.omniverse.nvidia.com/kit/docs/omni_usd_schema_physics/104.2/class_physx_schema_physx_scene_a_p_i.html
+  physx:
+    worker_thread_count: ${....num_threads}
+    solver_type: ${....solver_type}
+    use_gpu: ${eq:${....sim_device},"gpu"} # set to False to run on CPU
+    solver_position_iteration_count: 4
+    solver_velocity_iteration_count: 0
+    contact_offset: 0.02
+    rest_offset: 0.001
+    bounce_threshold_velocity: 0.2
+    friction_offset_threshold: 0.04
+    friction_correlation_distance: 0.025
+    enable_sleeping: True
+    enable_stabilization: True
+    max_depenetration_velocity: 100.0
+
+    # GPU buffers
+    gpu_max_rigid_contact_count: 524288
+    gpu_max_rigid_patch_count: 81920
+    gpu_found_lost_pairs_capacity: 1024
+    gpu_found_lost_aggregate_pairs_capacity: 262144
+    gpu_total_aggregate_pairs_capacity: 1024
+    gpu_max_soft_body_contacts: 1048576
+    gpu_max_particle_contacts: 1048576
+    gpu_heap_capacity: 67108864
+    gpu_temp_buffer_capacity: 16777216
+    gpu_max_num_partitions: 8
+
+  # each asset in the task can override physics parameters defined in the scene
+  # the name of the asset must match the name of the ArticulationView for the asset in the task
+  # additional Articulation and rigid body documentation can be found at https://docs.omniverse.nvidia.com/kit/docs/omni_usd_schema_physics/104.2/class_physx_schema_physx_articulation_a_p_i.html and https://docs.omniverse.nvidia.com/kit/docs/omni_usd_schema_physics/104.2/class_physx_schema_physx_rigid_body_a_p_i.html
+  Cartpole:
+    # a value of -1 means to use the same values defined in the physics scene
+    override_usd_defaults: False
+    enable_self_collisions: False
+    enable_gyroscopic_forces: True
+    # also in stage params
+    # per-actor
+    solver_position_iteration_count: 4
+    solver_velocity_iteration_count: 0
+    sleep_threshold: 0.005
+    stabilization_threshold: 0.001
+    # per-body
+    density: -1
+    max_depenetration_velocity: 100.0
+    # per-shape
+    contact_offset: 0.02
+    rest_offset: 0.001
\ No newline at end of file
diff --git a/omniisaacgymenvs/cfg/train/BipedPPO.yaml b/omniisaacgymenvs/cfg/train/BipedPPO.yaml
new file mode 100644
index 00000000..40a1828b
--- /dev/null
+++ b/omniisaacgymenvs/cfg/train/BipedPPO.yaml
@@ -0,0 +1,72 @@
+params:
+  seed: ${...seed}
+
+  algo:
+    name: a2c_continuous
+
+  model:
+    name: continuous_a2c_logstd
+
+  network:
+    name: actor_critic
+    separate: False
+    space:
+      continuous:
+        mu_activation: None
+        sigma_activation: None
+
+        mu_init:
+          name: default
+        sigma_init:
+          name: const_initializer
+          val: 0
+        fixed_sigma: True
+    mlp:
+      units: [400, 200, 100]    # can change
+      activation: elu
+      d2rl: False
+      
+      initializer:
+        name: default
+      regularizer:
+        name: None
+
+  load_checkpoint: ${if:${...checkpoint},True,False} # flag which sets whether to load the checkpoint
+  load_path: ${...checkpoint} # path to the checkpoint to load
+
+  config:
+    name: ${resolve_default:Biped,${....experiment}}
+    full_experiment_name: ${.name}
+    env_name: rlgpu
+    device: ${....rl_device}
+    device_name: ${....rl_device}
+    multi_gpu: ${....multi_gpu}
+    ppo: True
+    mixed_precision: True
+    normalize_input: True
+    normalize_value: True
+    value_bootstrap: True
+    num_actors: ${....task.env.numEnvs}
+    reward_shaper:
+      scale_value: 0.01
+    normalize_advantage: True
+    gamma: 0.99
+    tau: 0.95
+    learning_rate: 5e-5 # 5e-4
+    lr_schedule: adaptive
+    kl_threshold: 0.008
+    score_to_win: 20000
+    max_epochs: ${resolve_default:1000,${....max_iterations}}
+    save_best_after: 100
+    save_frequency: 100
+    grad_norm: 1.0
+    entropy_coef: 0.0
+    truncate_grads: True
+    e_clip: 0.2
+    horizon_length: 32
+    minibatch_size: 32768     
+    mini_epochs: 5
+    critic_coef: 4
+    clip_value: True
+    seq_length: 4
+    bounds_loss_coef: 0.0001
diff --git a/omniisaacgymenvs/cfg/train/BipedSAC.yaml b/omniisaacgymenvs/cfg/train/BipedSAC.yaml
new file mode 100644
index 00000000..db0b0a2c
--- /dev/null
+++ b/omniisaacgymenvs/cfg/train/BipedSAC.yaml
@@ -0,0 +1,51 @@
+params:  
+
+  seed: ${...seed}
+
+  algo:
+    name: sac
+
+  model:
+    name: soft_actor_critic
+
+  network:
+    name: soft_actor_critic
+    separate: True
+    space:
+      continuous:
+    mlp:
+      units: [512, 256]
+      activation: relu
+      
+      initializer:
+        name: default
+    log_std_bounds: [-5, 2]
+
+  load_checkpoint: ${if:${...checkpoint},True,False} # flag which sets whether to load the checkpoint
+  load_path: ${...checkpoint} # path to the checkpoint to load
+
+  config:
+    name: ${resolve_default:BipedSAC,${....experiment}}
+    env_name: rlgpu
+    device: ${....rl_device}
+    device_name: ${....rl_device}
+    multi_gpu: ${....multi_gpu}
+    normalize_input: True
+    reward_shaper:
+      scale_value: 1.0
+    max_epochs: ${resolve_default:50000,${....max_iterations}}
+    num_steps_per_episode: 8
+    save_best_after: 100
+    save_frequency: 1000
+    gamma: 0.99
+    init_alpha: 1.0
+    alpha_lr: 0.005
+    actor_lr: 0.0005
+    critic_lr: 0.0005
+    critic_tau: 0.005
+    batch_size: 4096
+    learnable_temperature: true
+    num_seed_steps: 5
+    num_warmup_steps: 10
+    replay_buffer_size: 1000000
+    num_actors: ${....task.env.numEnvs}
diff --git a/omniisaacgymenvs/cfg/train/HumanoidPPO.yaml b/omniisaacgymenvs/cfg/train/HumanoidPPO.yaml
index acc6c34f..2b2580fb 100644
--- a/omniisaacgymenvs/cfg/train/HumanoidPPO.yaml
+++ b/omniisaacgymenvs/cfg/train/HumanoidPPO.yaml
@@ -64,7 +64,7 @@ params:
     truncate_grads: True
     e_clip: 0.2
     horizon_length: 32
-    minibatch_size: 32768
+    minibatch_size: 32768 # = horizon_length * num_envs
     mini_epochs: 5
     critic_coef: 4
     clip_value: True
diff --git a/omniisaacgymenvs/cfg/train/MyCartpolePPO.yaml b/omniisaacgymenvs/cfg/train/MyCartpolePPO.yaml
new file mode 100644
index 00000000..ed50c3a4
--- /dev/null
+++ b/omniisaacgymenvs/cfg/train/MyCartpolePPO.yaml
@@ -0,0 +1,70 @@
+params:
+  seed: ${...seed}
+
+  algo:
+    name: a2c_continuous
+
+  model:
+    name: continuous_a2c_logstd
+
+  network:
+    name: actor_critic
+    separate: False
+    space:
+      continuous:
+        mu_activation: None
+        sigma_activation: None
+
+        mu_init:
+          name: default
+        sigma_init:
+          name: const_initializer
+          val: 0
+        fixed_sigma: True
+    mlp:
+      units: [32, 32]
+      activation: elu
+
+      initializer:
+        name: default
+      regularizer:
+        name: None
+
+  load_checkpoint: ${if:${...checkpoint},True,False} # flag which sets whether to load the checkpoint
+  load_path: ${...checkpoint} # path to the checkpoint to load
+
+  config:
+    name: ${resolve_default:MyCartpole,${....experiment}}
+    full_experiment_name: ${.name}
+    device: ${....rl_device}
+    device_name: ${....rl_device}
+    env_name: rlgpu
+    multi_gpu: ${....multi_gpu}
+    ppo: True
+    mixed_precision: False
+    normalize_input: True
+    normalize_value: True
+    num_actors: ${....task.env.numEnvs}
+    reward_shaper:
+      scale_value: 0.1
+    normalize_advantage: True
+    gamma: 0.99
+    tau: 0.95
+    learning_rate: 3e-4
+    lr_schedule: adaptive
+    kl_threshold: 0.008
+    score_to_win: 20000
+    max_epochs: ${resolve_default:100,${....max_iterations}}
+    save_best_after: 50
+    save_frequency: 25
+    grad_norm: 1.0
+    entropy_coef: 0.0
+    truncate_grads: True
+    e_clip: 0.2
+    horizon_length: 16
+    minibatch_size: 8192
+    mini_epochs: 8
+    critic_coef: 4
+    clip_value: True
+    seq_len: 4
+    bounds_loss_coef: 0.0001
\ No newline at end of file
diff --git a/omniisaacgymenvs/robots/articulations/anymal.py b/omniisaacgymenvs/robots/articulations/anymal.py
index 74c98a61..1dad917b 100644
--- a/omniisaacgymenvs/robots/articulations/anymal.py
+++ b/omniisaacgymenvs/robots/articulations/anymal.py
@@ -48,7 +48,7 @@ def __init__(
     ) -> None:
         """[summary]"""
 
-        self._usd_path = usd_path
+        self._usd_path = "/home/alex/Desktop/Collected_anymal_instanceable/omniverse-content-production.s3-us-west-2.amazonaws.com/Assets/Isaac/2023.1.0/Isaac/Robots/ANYbotics/anymal_instanceable.usd" # usd_path
         self._name = name
 
         if self._usd_path is None:
@@ -56,6 +56,7 @@ def __init__(
             if assets_root_path is None:
                 carb.log_error("Could not find nucleus server with /Isaac folder")
             self._usd_path = assets_root_path + "/Isaac/Robots/ANYbotics/anymal_instanceable.usd"
+        print("\n\n usd path: ", self._usd_path)
         add_reference_to_stage(self._usd_path, prim_path)
 
         super().__init__(
@@ -89,7 +90,7 @@ def set_anymal_properties(self, stage, prim):
         for link_prim in prim.GetChildren():
             if link_prim.HasAPI(PhysxSchema.PhysxRigidBodyAPI):
                 rb = PhysxSchema.PhysxRigidBodyAPI.Get(stage, link_prim.GetPrimPath())
-                rb.GetDisableGravityAttr().Set(False)
+                rb.GetDisableGravityAttr().Set(True)    # Changed!
                 rb.GetRetainAccelerationsAttr().Set(False)
                 rb.GetLinearDampingAttr().Set(0.0)
                 rb.GetMaxLinearVelocityAttr().Set(1000.0)
diff --git a/omniisaacgymenvs/robots/articulations/biped.py b/omniisaacgymenvs/robots/articulations/biped.py
new file mode 100644
index 00000000..8778cc2d
--- /dev/null
+++ b/omniisaacgymenvs/robots/articulations/biped.py
@@ -0,0 +1,69 @@
+# Copyright (c) 2018-2022, NVIDIA Corporation
+# All rights reserved.
+#
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions are met:
+#
+# 1. Redistributions of source code must retain the above copyright notice, this
+#    list of conditions and the following disclaimer.
+#
+# 2. Redistributions in binary form must reproduce the above copyright notice,
+#    this list of conditions and the following disclaimer in the documentation
+#    and/or other materials provided with the distribution.
+#
+# 3. Neither the name of the copyright holder nor the names of its
+#    contributors may be used to endorse or promote products derived from
+#    this software without specific prior written permission.
+#
+# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+
+from typing import Optional
+
+import carb
+import numpy as np
+import torch
+from omni.isaac.core.robots.robot import Robot
+from omni.isaac.core.utils.nucleus import get_assets_root_path
+from omni.isaac.core.utils.stage import add_reference_to_stage
+from pxr import PhysxSchema
+
+
+class Biped(Robot):
+    def __init__(
+        self,
+        prim_path: str,
+        name: Optional[str] = "Biped",
+        usd_path: Optional[str] = None,
+        translation: Optional[np.ndarray] = None,
+        orientation: Optional[np.ndarray] = None,
+    ) -> None:
+
+        self._usd_path = "/home/alex/Desktop/biped_schematics/biped_schematics/biped_schematics.usd" # usd_path
+        self._name = name
+
+        if self._usd_path is None:
+            print('no path')
+            assets_root_path = get_assets_root_path()
+            if assets_root_path is None:
+                carb.log_error("Could not find Isaac Sim assets folder")
+            self._usd_path = assets_root_path + "/Isaac/Robots/Cartpole/cartpole.usd"
+
+        add_reference_to_stage(self._usd_path, prim_path)
+
+        super().__init__(
+            prim_path=prim_path,
+            name=name,
+            translation=translation,
+            orientation=orientation,
+            articulation_controller=None,
+        )
\ No newline at end of file
diff --git a/omniisaacgymenvs/robots/articulations/cartpole.py b/omniisaacgymenvs/robots/articulations/cartpole.py
index 5287d3b8..4d0b596a 100644
--- a/omniisaacgymenvs/robots/articulations/cartpole.py
+++ b/omniisaacgymenvs/robots/articulations/cartpole.py
@@ -55,6 +55,7 @@ def __init__(
             if assets_root_path is None:
                 carb.log_error("Could not find Isaac Sim assets folder")
             self._usd_path = assets_root_path + "/Isaac/Robots/Cartpole/cartpole.usd"
+            print("\n\nusd path: ", self._usd_path)
 
         add_reference_to_stage(self._usd_path, prim_path)
 
diff --git a/omniisaacgymenvs/robots/articulations/humanoid.py b/omniisaacgymenvs/robots/articulations/humanoid.py
index 09f45de1..3cd12896 100644
--- a/omniisaacgymenvs/robots/articulations/humanoid.py
+++ b/omniisaacgymenvs/robots/articulations/humanoid.py
@@ -42,7 +42,7 @@ def __init__(
         self,
         prim_path: str,
         name: Optional[str] = "Humanoid",
-        usd_path: Optional[str] = None,
+        usd_path: Optional[str] = None,             # "/home/alex/Desktop/humanoid.usd",
         translation: Optional[np.ndarray] = None,
         orientation: Optional[np.ndarray] = None,
     ) -> None:
@@ -55,6 +55,7 @@ def __init__(
             if assets_root_path is None:
                 carb.log_error("Could not find Isaac Sim assets folder")
             self._usd_path = assets_root_path + "/Isaac/Robots/Humanoid/humanoid_instanceable.usd"
+            print("usd path: ", self._usd_path)
 
         add_reference_to_stage(self._usd_path, prim_path)
 
@@ -64,4 +65,4 @@ def __init__(
             translation=translation,
             orientation=orientation,
             articulation_controller=None,
-        )
+        )
\ No newline at end of file
diff --git a/omniisaacgymenvs/scripts/rlgames_train.py b/omniisaacgymenvs/scripts/rlgames_train.py
old mode 100644
new mode 100755
diff --git a/omniisaacgymenvs/tasks/base/rl_task.py b/omniisaacgymenvs/tasks/base/rl_task.py
index ad7d8d79..932d321f 100644
--- a/omniisaacgymenvs/tasks/base/rl_task.py
+++ b/omniisaacgymenvs/tasks/base/rl_task.py
@@ -73,6 +73,10 @@ def __init__(self, name, env, offset=None) -> None:
         self.test = self._cfg["test"]
         self._device = self._cfg["sim_device"]
 
+        # ADDED LOG PATH
+        self._log = f"runs/{self._cfg['experiment']}/{self._cfg['experiment']}.txt"
+        self._step = 0
+
         # set up randomizer for DR
         self._dr_randomizer = Randomizer(self._cfg, self._task_cfg)
         if self._dr_randomizer.randomize:
@@ -251,6 +255,20 @@ def post_physics_step(self):
             self.is_done()
             self.get_extras()
 
+            if self._step % 100 == 0:
+                with open(self._log, "a") as log_file:                                     # ADDED LOGGING
+                    log_file.write(f"Step {self._step}:\n")
+                    log_file.write(f"Ave Reward: {self.log_arr[0]}\n")
+                    log_file.write(f"Progress Reward: {self.log_arr[1]}\n")
+                    log_file.write(f"Alive Reward: {self.log_arr[2]}\n")
+                    log_file.write(f"Up Reward: {self.log_arr[3]}\n")
+                    log_file.write(f"Heading Reward: {self.log_arr[4]}\n")
+                    log_file.write(f"Action Cost: {self.log_arr[5]}\n")
+                    log_file.write(f"Energy Cost: {self.log_arr[6]}\n")
+                    log_file.write(f"DOF Limit Cost: {self.log_arr[7]}\n")
+                    log_file.write(f"Speed Reward: {self.log_arr[8]}\n")
+            self._step += 1
+
         return self.obs_buf, self.rew_buf, self.reset_buf, self.extras
 
 class RLTaskWarp(RLTask):
diff --git a/omniisaacgymenvs/tasks/biped.py b/omniisaacgymenvs/tasks/biped.py
new file mode 100644
index 00000000..dadf3953
--- /dev/null
+++ b/omniisaacgymenvs/tasks/biped.py
@@ -0,0 +1,132 @@
+# Copyright (c) 2018-2022, NVIDIA Corporation
+# All rights reserved.
+#
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions are met:
+#
+# 1. Redistributions of source code must retain the above copyright notice, this
+#    list of conditions and the following disclaimer.
+#
+# 2. Redistributions in binary form must reproduce the above copyright notice,
+#    this list of conditions and the following disclaimer in the documentation
+#    and/or other materials provided with the distribution.
+#
+# 3. Neither the name of the copyright holder nor the names of its
+#    contributors may be used to endorse or promote products derived from
+#    this software without specific prior written permission.
+#
+# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+
+import math
+
+import numpy as np
+import torch
+from omni.isaac.core.articulations import ArticulationView
+from omni.isaac.core.utils.prims import get_prim_at_path
+from omni.isaac.core.utils.torch.maths import tensor_clamp, torch_rand_float, unscale
+from omni.isaac.core.utils.torch.rotations import compute_heading_and_up, compute_rot, quat_conjugate
+from omniisaacgymenvs.tasks.base.rl_task import RLTask
+from omniisaacgymenvs.robots.articulations.biped import Biped
+from omniisaacgymenvs.tasks.shared.locomotion import LocomotionTask
+from pxr import PhysxSchema
+
+
+class BipedLocomotionTask(LocomotionTask):
+    def __init__(self, name, sim_config, env, offset=None) -> None:
+        self.update_config(sim_config)
+        self._num_observations = 60                             # ? position, orientation, linear and angular velocity
+        self._num_actions = 12                                  
+        self._humanoid_positions = torch.tensor([0, 0, 1.1])   # start height
+
+        LocomotionTask.__init__(self, name=name, env=env)
+        return
+
+    def update_config(self, sim_config):
+        self._sim_config = sim_config
+        self._cfg = sim_config.config
+        self._task_cfg = sim_config.task_config
+        LocomotionTask.update_config(self)
+
+    def set_up_scene(self, scene) -> None:
+        self.get_humanoid()
+        RLTask.set_up_scene(self, scene)
+        self._humanoids = ArticulationView(                 
+            prim_paths_expr="/World/envs/.*/biped_schematics/base_link", name="biped_view", reset_xform_properties=False
+        )
+        scene.add(self._humanoids)
+        return
+
+    def initialize_views(self, scene):
+        RLTask.initialize_views(self, scene)
+        if scene.object_exists("biped_view"):
+            scene.remove_object("biped_view", registry_only=True)
+        self._humanoids = ArticulationView(
+            prim_paths_expr="/World/envs/.*/biped_schematics/base_link", name="biped_view", reset_xform_properties=False
+        )
+        scene.add(self._humanoids)
+
+    def get_humanoid(self):
+        humanoid = Biped(                 # change
+            prim_path=self.default_zero_env_path + "/biped_schematics", name="Biped", translation=self._humanoid_positions
+        )
+        self._sim_config.apply_articulation_settings(
+            "Biped", get_prim_at_path(humanoid.prim_path), self._sim_config.parse_actor_config("Biped")
+        )
+
+    def get_robot(self):
+        return self._humanoids
+
+    def post_reset(self):   # TODO: change
+        self.joint_gears = torch.tensor(
+            [
+                67.5000,  # hip_x_left
+                67.5000,  # hip_x_right
+                67.5000,  # hip_z_left
+                67.5000,  # hip_z_right
+                67.5000,  # hip_y_left
+                67.5000,  # hip_y_right
+                90.0000,  # knee_left
+                90.0000,  # knee_right
+                22.5000,  # ankle_y_left
+                22.5000,  # ankle_y_right
+                22.5000,  # ankle_x_left
+                22.5000,  # ankle_x_right
+            ],
+            device=self._device,
+        )
+        self.max_motor_effort = torch.max(self.joint_gears)
+        self.motor_effort_ratio = self.joint_gears / self.max_motor_effort
+        dof_limits = self._humanoids.get_dof_limits()
+        self.dof_limits_lower = dof_limits[0, :, 0].to(self._device)
+        self.dof_limits_upper = dof_limits[0, :, 1].to(self._device)
+
+        force_links = ["foot_1", "foot_2"]      # TODO: changed
+        self._sensor_indices = torch.tensor(
+            [self._humanoids._body_indices[j] for j in force_links], device=self._device, dtype=torch.long
+        )
+
+        LocomotionTask.post_reset(self)
+
+    def get_dof_at_limit_cost(self):
+        return get_dof_at_limit_cost(self.obs_buf, self.motor_effort_ratio, self.joints_at_limit_cost_scale)
+
+
+@torch.jit.script
+def get_dof_at_limit_cost(obs_buf, motor_effort_ratio, joints_at_limit_cost_scale):
+    # type: (Tensor, Tensor, float) -> Tensor
+    scaled_cost = joints_at_limit_cost_scale * (torch.abs(obs_buf[:, 12:24]) - 0.98) / 0.02     # TODO: change idx in obs_buf
+    
+    dof_at_limit_cost = torch.sum(
+        (torch.abs(obs_buf[:, 12:24]) > 0.98) * scaled_cost * motor_effort_ratio.unsqueeze(0), dim=-1
+    )
+    return dof_at_limit_cost
diff --git a/omniisaacgymenvs/tasks/humanoid.py b/omniisaacgymenvs/tasks/humanoid.py
index a590446c..6eee01a9 100644
--- a/omniisaacgymenvs/tasks/humanoid.py
+++ b/omniisaacgymenvs/tasks/humanoid.py
@@ -46,7 +46,7 @@ def __init__(self, name, sim_config, env, offset=None) -> None:
 
         self.update_config(sim_config)
         self._num_observations = 87
-        self._num_actions = 21
+        self._num_actions = 21                                  # num drive under joints
         self._humanoid_positions = torch.tensor([0, 0, 1.34])
 
         LocomotionTask.__init__(self, name=name, env=env)
@@ -80,6 +80,7 @@ def get_humanoid(self):
         humanoid = Humanoid(
             prim_path=self.default_zero_env_path + "/Humanoid", name="Humanoid", translation=self._humanoid_positions
         )
+        print("humaoid prim path: ", humanoid.prim_path)
         self._sim_config.apply_articulation_settings(
             "Humanoid", get_prim_at_path(humanoid.prim_path), self._sim_config.parse_actor_config("Humanoid")
         )
diff --git a/omniisaacgymenvs/tasks/my_cartpole.py b/omniisaacgymenvs/tasks/my_cartpole.py
new file mode 100644
index 00000000..da30aeab
--- /dev/null
+++ b/omniisaacgymenvs/tasks/my_cartpole.py
@@ -0,0 +1,176 @@
+import math
+import torch
+from omniisaacgymenvs.tasks.base.rl_task import RLTask
+from omni.isaac.core.articulations import ArticulationView
+from omni.isaac.core.utils.prims import get_prim_at_path
+from omniisaacgymenvs.robots.articulations.cartpole import Cartpole
+
+class MyCartpoleTask(RLTask):
+    def __init__(self, name, sim_config, env, offset=None) -> None:
+        """
+        name: parsed from task config yaml file
+        sim_config: SimConfig obj with task and physics params
+        env: environment obj from rlgames_train.py
+        all parsed by task_util.py
+        """
+        self.update_config(sim_config)
+        self._max_episode_length = 500
+
+        # must be defined in task class
+        self._num_observations = 4      # cart pos, cart vel, pole ang, pole ang vel
+        self._num_actions = 1           # apply force to cart
+
+        # call parent class constructor for RL variables
+        RLTask.__init__(self, name, env)
+        return
+    
+    def update_config(self, sim_config):
+        # extract task config from main config dictionary
+        self._sim_config = sim_config
+        self._cfg = sim_config.config
+        self._task_cfg = sim_config.task_config
+
+        # parse task config parameters
+        self._num_envs = self._task_cfg["env"]["numEnvs"]
+        self._env_spacing = self._task_cfg["env"]["envSpacing"]
+        self._cartpole_positions = torch.tensor([0.0, 0.0, 2.0])        # x, y, z?
+
+        # reset and actions related variables
+        self._reset_dist = self._task_cfg["env"]["resetDist"]
+        self._max_push_effort = self._task_cfg["env"]["maxEffort"]
+        return
+
+    def set_up_scene(self, scene) -> None:
+        # first create a single environment
+        self.get_cartpole()
+
+        # call the parent class to clone the single environment
+        super().set_up_scene(scene)
+
+        # construct an ArticulationView object to hold our collection of environments
+        self._cartpoles = ArticulationView(                             # NEED TO REVIEW
+            prim_paths_expr="/World/envs/.*/Cartpole", name="cartpole_view", reset_xform_properties=False
+        )
+
+        # register the ArticulationView object to the world, so that it can be initialized
+        scene.add(self._cartpoles)
+        return
+
+    def get_cartpole(self):
+        # add a single robot to the stage
+        cartpole = Cartpole(                                            # NEED TO REVIEW
+            prim_path=self.default_zero_env_path + "/Cartpole", name="Cartpole", translation=self._cartpole_positions
+        )
+
+        # applies articulation settings from the task configuration yaml file
+        self._sim_config.apply_articulation_settings(
+            "Cartpole", get_prim_at_path(cartpole.prim_path), self._sim_config.parse_actor_config("Cartpole")
+        )
+        return
+    
+    def post_reset(self):
+        # retrieve cart and pole joint indices
+        self._cart_dof_idx = self._cartpoles.get_dof_index("cartJoint")
+        self._pole_dof_idx = self._cartpoles.get_dof_index("poleJoint")
+
+        # randomize all envs
+        indices = torch.arange(self._cartpoles.count, dtype=torch.int64, device=self._device)
+        self.reset_idx(indices)
+        return
+
+    def reset_idx(self, env_ids):
+        num_resets = len(env_ids)
+
+        # randomize DOF positions
+        dof_pos = torch.zeros((num_resets, self._cartpoles.num_dof), device=self._device)
+        dof_pos[:, self._cart_dof_idx] = 1.0 * (1.0 - 2.0 * torch.rand(num_resets, device=self._device))
+        dof_pos[:, self._pole_dof_idx] = 0.125 * math.pi * (1.0 - 2.0 * torch.rand(num_resets, device=self._device))
+
+        # randomize DOF velocities
+        dof_vel = torch.zeros((num_resets, self._cartpoles.num_dof), device=self._device)
+        dof_vel[:, self._cart_dof_idx] = 0.5 * (1.0 - 2.0 * torch.rand(num_resets, device=self._device))
+        dof_vel[:, self._pole_dof_idx] = 0.25 * math.pi * (1.0 - 2.0 * torch.rand(num_resets, device=self._device))
+
+        # apply randomized joint positions and velocities to environments
+        indices = env_ids.to(dtype=torch.int32)
+        self._cartpoles.set_joint_positions(dof_pos, indices=indices)
+        self._cartpoles.set_joint_velocities(dof_vel, indices=indices)
+
+        # reset the reset buffer and progress buffer after applying reset
+        self.reset_buf[env_ids] = 0
+        self.progress_buf[env_ids] = 0
+        return
+
+    def pre_physics_step(self, actions) -> None:
+        # make sure simulation has not been stopped from the UI
+        if not self._env._world.is_playing():
+            return
+
+        # extract environment indices that need reset and reset them
+        reset_env_ids = self.reset_buf.nonzero(as_tuple=False).squeeze(-1)
+        if len(reset_env_ids) > 0:
+            self.reset_idx(reset_env_ids)
+
+        # make sure actions buffer is on the same device as the simulation
+        actions = actions.to(self._device)
+
+        # compute forces from the actions
+        forces = torch.zeros((self._cartpoles.count, self._cartpoles.num_dof), dtype=torch.float32, device=self._device)
+        forces[:, self._cart_dof_idx] = self._max_push_effort * actions[:, 0]
+
+        # apply actions to all of the environments
+        indices = torch.arange(self._cartpoles.count, dtype=torch.int32, device=self._device)
+        self._cartpoles.set_joint_efforts(forces, indices=indices)
+        return
+
+    def get_observations(self) -> dict:
+        # retrieve joint positions and velocities
+        dof_pos = self._cartpoles.get_joint_positions(clone=False)
+        dof_vel = self._cartpoles.get_joint_velocities(clone=False)
+
+        # extract joint states for the cart and pole joints
+        cart_pos = dof_pos[:, self._cart_dof_idx]
+        cart_vel = dof_vel[:, self._cart_dof_idx]
+        pole_pos = dof_pos[:, self._pole_dof_idx]
+        pole_vel = dof_vel[:, self._pole_dof_idx]
+
+        # populate the observations buffer
+        self.obs_buf[:, 0] = cart_pos
+        self.obs_buf[:, 1] = cart_vel
+        self.obs_buf[:, 2] = pole_pos
+        self.obs_buf[:, 3] = pole_vel
+
+        # construct the observations dictionary and return
+        observations = {self._cartpoles.name: {"obs_buf": self.obs_buf}}
+        return observations
+    
+    def calculate_metrics(self) -> None:
+        # use states from the observation buffer to compute reward
+        cart_pos = self.obs_buf[:, 0]
+        cart_vel = self.obs_buf[:, 1]
+        pole_angle = self.obs_buf[:, 2]
+        pole_vel = self.obs_buf[:, 3]
+
+        # define the reward function based on pole angle and robot velocities
+        reward = 1.0 - pole_angle * pole_angle - 0.01 * torch.abs(cart_vel) - 0.5 * torch.abs(pole_vel)
+        # penalize the policy if the cart moves too far on the rail
+        reward = torch.where(torch.abs(cart_pos) > self._reset_dist, torch.ones_like(reward) * -2.0, reward)
+        # penalize the policy if the pole moves beyond 90 degrees
+        reward = torch.where(torch.abs(pole_angle) > math.pi / 2, torch.ones_like(reward) * -2.0, reward)
+
+        # assign rewards to the reward buffer
+        self.rew_buf[:] = reward
+        return
+
+    def is_done(self) -> None:
+        cart_pos = self.obs_buf[:, 0]
+        pole_pos = self.obs_buf[:, 2]
+
+        # check for which conditions are met and mark the environments that satisfy the conditions
+        resets = torch.where(torch.abs(cart_pos) > self._reset_dist, 1, 0)
+        resets = torch.where(torch.abs(pole_pos) > math.pi / 2, 1, resets)
+        resets = torch.where(self.progress_buf >= self._max_episode_length, 1, resets)
+
+        # assign the resets to the reset buffer
+        self.reset_buf[:] = resets
+        return
\ No newline at end of file
diff --git a/omniisaacgymenvs/tasks/shared/locomotion.py b/omniisaacgymenvs/tasks/shared/locomotion.py
index 4dcc0637..645319f8 100644
--- a/omniisaacgymenvs/tasks/shared/locomotion.py
+++ b/omniisaacgymenvs/tasks/shared/locomotion.py
@@ -63,6 +63,10 @@ def update_config(self):
         self.death_cost = self._task_cfg["env"]["deathCost"]
         self.termination_height = self._task_cfg["env"]["terminationHeight"]
         self.alive_reward_scale = self._task_cfg["env"]["alive_reward_scale"]
+        self.progress_reward = self._task_cfg["env"]["progress_reward"]         # added
+        self.speed_weight = self._task_cfg["env"]["speedWeight"]         # added
+        self.termination_heading = self._task_cfg["env"]["terminationHeading"]         # added
+        self.termination_up = self._task_cfg["env"]["terminationUp"]         # added
 
     @abstractmethod
     def set_up_scene(self, scene) -> None:
@@ -188,26 +192,43 @@ def post_reset(self):
         self.reset_idx(indices)
 
     def calculate_metrics(self) -> None:
-        self.rew_buf[:] = calculate_metrics(
-            self.obs_buf,
-            self.actions,
-            self.up_weight,
-            self.heading_weight,
-            self.potentials,
-            self.prev_potentials,
-            self.actions_cost_scale,
-            self.energy_cost_scale,
-            self.termination_height,
-            self.death_cost,
-            self._robots.num_dof,
-            self.get_dof_at_limit_cost(),
-            self.alive_reward_scale,
-            self.motor_effort_ratio,
-        )
+        self.rew_buf[:], self.log_arr = calculate_metrics(
+                                                self.obs_buf,
+                                                self.actions,
+                                                self.up_weight,
+                                                self.heading_weight,
+                                                self.potentials,
+                                                self.prev_potentials,
+                                                self.actions_cost_scale,
+                                                self.energy_cost_scale,
+                                                self.termination_height,
+                                                self.death_cost,
+                                                self._robots.num_dof,
+                                                self.get_dof_at_limit_cost(),
+                                                self.alive_reward_scale,
+                                                self.motor_effort_ratio,
+                                                self.progress_reward,           # added
+                                                self.speed_weight,
+                                                self.termination_heading,
+                                                self.termination_up,
+                                            )
+
+        self.log_arr = [np.mean(self.log_arr[0].cpu().numpy()),
+                        np.mean(self.log_arr[1].cpu().numpy()),
+                        np.mean(self.log_arr[2].cpu().numpy()),
+                        np.mean(self.log_arr[3].cpu().numpy()),
+                        np.mean(self.log_arr[4].cpu().numpy()),
+                        np.mean(self.log_arr[5].cpu().numpy()),
+                        np.mean(self.log_arr[6].cpu().numpy()),
+                        np.mean(self.log_arr[7].cpu().numpy()),
+                        np.mean(self.log_arr[8].cpu().numpy()),
+                        ]
+
+        
 
     def is_done(self) -> None:
         self.reset_buf[:] = is_done(
-            self.obs_buf, self.termination_height, self.reset_buf, self.progress_buf, self._max_episode_length
+            self.obs_buf, self.termination_height, self.termination_up, self.termination_heading , self.reset_buf, self.progress_buf, self._max_episode_length
         )
 
 
@@ -285,9 +306,11 @@ def get_observations(
 
 
 @torch.jit.script
-def is_done(obs_buf, termination_height, reset_buf, progress_buf, max_episode_length):
-    # type: (Tensor, float, Tensor, Tensor, float) -> Tensor
+def is_done(obs_buf, termination_height, termination_up, termination_heading, reset_buf, progress_buf, max_episode_length):
+    # type: (Tensor, float, float, float, Tensor, Tensor, float) -> Tensor
     reset = torch.where(obs_buf[:, 0] < termination_height, torch.ones_like(reset_buf), reset_buf)
+    reset = torch.where(obs_buf[:, 11] < termination_heading, torch.ones_like(reset_buf), reset)                    # added to walk straight
+    reset = torch.where(obs_buf[:, 10] < termination_up, torch.ones_like(reset_buf), reset)                    # added to walk straight
     reset = torch.where(progress_buf >= max_episode_length - 1, torch.ones_like(reset_buf), reset)
     return reset
 
@@ -308,8 +331,12 @@ def calculate_metrics(
     dof_at_limit_cost,
     alive_reward_scale,
     motor_effort_ratio,
+    progress_reward,            # added
+    speed_weight,               # added
+    termination_heading,        # added
+    termination_up,             # added
 ):
-    # type: (Tensor, Tensor, float, float, Tensor, Tensor, float, float, float, float, int, Tensor, float, Tensor) -> Tensor
+    # type: (Tensor, Tensor, float, float, Tensor, Tensor, float, float, float, float, int, Tensor, float, Tensor, float, float, float, float) -> Tuple[Tensor, List[Tensor]]
 
     heading_weight_tensor = torch.ones_like(obs_buf[:, 11]) * heading_weight
     heading_reward = torch.where(obs_buf[:, 11] > 0.8, heading_weight_tensor, heading_weight * obs_buf[:, 11] / 0.8)
@@ -326,10 +353,12 @@ def calculate_metrics(
 
     # reward for duration of staying alive
     alive_reward = torch.ones_like(potentials) * alive_reward_scale
-    progress_reward = potentials - prev_potentials
+    progress_reward = (potentials - prev_potentials) * progress_reward              # TODO: ADDED PROGRESS MULTIPLIER
+    speed_reward = obs_buf[:, 1] * speed_weight
 
     total_reward = (
-        progress_reward
+        progress_reward 
+        + speed_reward
         + alive_reward
         + up_reward
         + heading_reward
@@ -337,9 +366,34 @@ def calculate_metrics(
         - energy_cost_scale * electricity_cost
         - dof_at_limit_cost
     )
+    pre_penalty = total_reward.clone().detach()
+
 
     # adjust reward for fallen agents
+    # CHANGED
     total_reward = torch.where(
         obs_buf[:, 0] < termination_height, torch.ones_like(total_reward) * death_cost, total_reward
     )
-    return total_reward
+    total_reward = torch.where(
+        obs_buf[:, 11] < termination_heading, torch.ones_like(total_reward) * death_cost, total_reward
+    )
+    total_reward = torch.where(
+        obs_buf[:, 10] < termination_up, torch.ones_like(total_reward) * death_cost, total_reward
+    )
+
+    alive_dead = total_reward - pre_penalty
+    
+
+    # CHANGED FOR LOGGING
+    log_arr = [total_reward,
+               progress_reward,
+               alive_dead,        # change to be diff between before and after applying penalty
+               up_reward,
+               heading_reward,
+               actions_cost_scale * actions_cost,
+               energy_cost_scale * electricity_cost,
+               dof_at_limit_cost,
+               speed_reward,
+               ]
+
+    return total_reward, log_arr
diff --git a/omniisaacgymenvs/utils/config_utils/sim_config.py b/omniisaacgymenvs/utils/config_utils/sim_config.py
index c49c04fa..07637e5b 100644
--- a/omniisaacgymenvs/utils/config_utils/sim_config.py
+++ b/omniisaacgymenvs/utils/config_utils/sim_config.py
@@ -100,6 +100,7 @@ def _parse_config(self):
         sim_cfg = self._cfg.get("sim", None)
         if sim_cfg is not None:
             for opt in sim_cfg.keys():
+                print('     ', opt)
                 if opt in self._sim_params:
                     if opt == "default_physics_material":
                         for material_opt in sim_cfg[opt]:
@@ -114,6 +115,7 @@ def _parse_config(self):
         self._physx_params = copy.deepcopy(default_physx_params)
         if sim_cfg is not None and "physx" in sim_cfg:
             for opt in sim_cfg["physx"].keys():
+                print('     ', opt)
                 if opt in self._physx_params:
                     self._physx_params[opt] = sim_cfg["physx"][opt]
                 else:
diff --git a/omniisaacgymenvs/utils/task_util.py b/omniisaacgymenvs/utils/task_util.py
index 3b154e8e..d014dc81 100644
--- a/omniisaacgymenvs/utils/task_util.py
+++ b/omniisaacgymenvs/utils/task_util.py
@@ -50,6 +50,8 @@ def import_tasks():
     from omniisaacgymenvs.tasks.warp.cartpole import CartpoleTask as CartpoleTaskWarp
     from omniisaacgymenvs.tasks.warp.humanoid import HumanoidLocomotionTask as HumanoidLocomotionTaskWarp
 
+    from omniisaacgymenvs.tasks.biped import BipedLocomotionTask
+    from omniisaacgymenvs.tasks.my_cartpole import MyCartpoleTask
     # Mappings from strings to environments
     task_map = {
         "AllegroHand": AllegroHandTask,
@@ -71,6 +73,8 @@ def import_tasks():
         "ShadowHand": ShadowHandTask,
         "ShadowHandOpenAI_FF": ShadowHandTask,
         "ShadowHandOpenAI_LSTM": ShadowHandTask,
+        "Biped": BipedLocomotionTask,
+        "MyCartpole": MyCartpoleTask,
     }
 
     task_map_warp = {
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diff --git a/test.py b/test.py
new file mode 100644
index 00000000..b2593065
--- /dev/null
+++ b/test.py
@@ -0,0 +1,51 @@
+import matplotlib.pyplot as plt
+import pandas as pd
+
+# basic params
+experiment = "Biped_07"
+file = f"{experiment}.txt"
+col_names = ["Ave Reward", "Progress Reward", "Alive Reward",
+              "Up Reward", "Heading Reward", "Action Cost",
+              "Energy Cost", "DOF Limit Cost"]
+
+# parse log and make pd df
+df = []
+with open(file, 'r') as f:
+    row = []
+    for line in f:
+        split = line.split(":")
+        rew_type, val = split[0], split[1].strip()
+        
+        if rew_type[:4] != "Step":
+            row.append(float(val))
+        else:
+            df.append(row)
+            row = []
+
+df = pd.DataFrame(df[1:][:])
+df.columns = col_names
+df = df.reset_index()
+
+# plot
+# Create a bar chart for stacked categories
+fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(15, 6))
+# fig, ax1 = plt.subplots(figsize=(10, 6))
+stacked_cols = col_names[1:]
+stacked_cols.append('index')
+line_cols = ['Ave Reward', 'index']
+
+df[stacked_cols].plot(x='index', kind='bar', stacked=True, ax=ax1)
+ax1.set_xlabel('Episode Num * 100')
+ax1.tick_params(axis='x', labelsize=5)
+ax1.set_ylabel('Reward Components')
+ax1.legend(loc='center left', bbox_to_anchor=(1, 0.5))
+
+# Create a line plot for 'Ave Reward'
+df[line_cols].plot(x='index', kind='line', color='black', marker='o', ax=ax2)
+ax2.set_xlabel('Episode Num * 100')
+ax2.set_ylabel('Ave Reward')
+
+plt.tight_layout()
+plt.savefig(f"{experiment}.png")
+plt.show()
+
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