samucox / bandits-codes

Bandits codes contributed by Louie Hoang at MSR.

bandits-codes

Folders

* louie-experiments

Bandits codes contributed by Louie Hoang at MSR.

* bandit_rl_implementations

Bandits codes for algorithms like UCB,TS etc. and analyses written by me. Could include implementations of papers and tutorials.

Directory Structure

bandits-codes
├── README.md
├── bandit_rl_implementations
│   ├── Bandits_email_version.py
│   ├── CBThompsonSampling_LogisticReg.py
│   ├── MAB_TS_posteriors.png
│   ├── TS_Loss_ER.png
│   ├── versions=10_ignore_regret.png
│   └── versions=3,T=1000.png
└── louie_experiments
    ├── LinUCB.py
    ├── bandit_data_format.py
    ├── base_model.py
    ├── beta_bernoulli.py
    ├── data_reader.py
    ├── driver.py
    ├── driver_contextual.py
    ├── driver_gaussian_rewards.py
    ├── driver_gaussian_rewards_two_bandits.py
    ├── driver_two_bandits.py
    ├── driver_two_bandits_contextual.py
    ├── epsilonGreedyPolicy.py
    ├── epsilon_greedy.py
    ├── forced_actions.py
    ├── gaussian_reward.py
    ├── generate_single_bandit.py
    ├── greedy_model.py
    ├── logistic_regression.py
    ├── logistic_regression_scikit.py
    ├── ng_normal.py
    ├── nig_normal.py
    ├── output_format.py
    ├── plot_graph.py
    ├── queueBasedBandit.py
    ├── random_policy.py
    ├── test_logistic_regression.py
    ├── thompson_ng_policy.py
    ├── thompson_nig_policy.py
    ├── thompson_policy.py
    ├── two_factor_reward.py
    └── ucb1.py