<jupyter_start><jupyter_text>Parameter settingcentered distributed with equal distance<jupyter_code>reps = 10 # number of repeated runs for a single agent
horizon = 2000000

Ns = [2, 3, 4]
Delta = 0.1

t = time.time()
for N in Ns:
    p_dist = centered_equal_distance(N, Delta)
    agents = [ESCB(n_pairs=N)]
    results = matching_selection_sim(agents, p_dist, horizon, reps)
    print(results)
        
print('------------- Escaped time is {0} seconds -------------'.format(time.time() - t))<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.15678776290630975, 'fraction_numerical': 0.028680688336520075, 'mean_word_length': 3.5172413793103448, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, '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': '419780', 'license': 'MIT', 'n_tokens_mistral': 190, 'n_tokens_neox': 175, 'n_words': 48, 'path': 'experiments/ESCB_experiements.ipynb', 'repo_name': 'jialinyi94/matching-bandit', 'size': '523'}