rlcmab-sampler 1.0.1

Gaussian reward sampler for Contextual Bandit news recommendation system

rlcmab-sampler

A reward sampler for Contextual Bandit news recommendation systems.

Installation

pip install rlcmab-sampler

Quick Start

from sampler import sampler

# Initialize with your roll number (i)
reward_sampler = sampler(i=42)

# Get a reward from arm j
reward = reward_sampler.sample(j=5)
print(reward)

# Sample a few arms
for j in range(3):
    print(j, reward_sampler.sample(j))

API Reference

sampler(i, n_arms=12)

Initialize a new sampler instance.

Parameters:

• i (int): Student ID used to seed the random number generator
• n_arms (int, optional): Number of arms/articles. Default: 12

Attributes:

• means: List of mean values for each Gaussian distribution
• stds: List of standard deviations for each Gaussian distribution
• distributions: List of scipy.stats.norm distribution objects

sample(j)

Sample a reward from the specified arm.

Parameters:

• j (int): Arm index (must be between 0 and 11)

Returns:

• float: Reward value sampled from the arm's Gaussian distribution

Raises:

• ValueError: If j is not in the valid range [0, 11]

Reproducibility

For the same student ID i, the generated arm distributions remain the same across runs. Different student IDs map to different distributions.

License

MIT License