<jupyter_start><jupyter_text>Name: <NAME>
 Roll No.: 190816
 Email: <EMAIL>  Problem 1: Random-Maze Environment Implementation<jupyter_code>!pip install -e .
import gym 
import numpy as np
import matplotlib.pyplot as plt
rme = gym.make('midsem.envs:RME-v0')
print(rme)
print(rme.observation_space)
print(rme.action_space)
print(rme.maze)
print(rme.maze.shape)
print(rme.hole_loc)
print(rme.goal_loc)
print(rme.wall_loc)
print(rme.hole_reward)
print(rme.goal_reward)
print(rme.step_reward)
print(rme.prob)
rme.reset(start_loc=0)
rme.render()
rme.step(1)
rme.render()
rme.step(1)
rme.render()
rme.step(1)
rme.render()
rme.step(1)
rme.render()
print(rme.trace)
rme.reset(start_loc=0)
rme.render()
rme.step(1)
rme.render()
rme.step(1)
rme.render()
rme.step(2)
rme.render()
rme.step(1)
rme.render()
print(rme.trace)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.15693012600229095, 'fraction_numerical': 0.020618556701030927, 'mean_word_length': 5.198581560283688, 'pattern_counts': {'":': 0, '<': 7, '<?xml version=': 0, '>': 7, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '433886', 'license': 'MIT', 'n_tokens_mistral': 401, 'n_tokens_neox': 422, 'n_words': 60, 'path': 'MIDSEM/midsem/Q1_main.ipynb', 'repo_name': 'ShivenTripathi/CS698-Deep-Reinforcement-Learning', 'size': '892'}