Current collected state Current
Observed since 20 Oct, 17:25 UTC
No superseded metadata states collected. Unchanged observations do not create new revisions.
Reinforcement learning demos and utilities
Small reinforcement learning demos built on gymnasium.
pip install abijith-rl
import abijith_rl as rl
mc_df = rl.montecarlo_code(num_episodes=200)
print(mc_df.head())
# Prints the full demo code string
rl.montecarlo()
td_df = rl.td_prediction(num_episodes=50)
print(td_df.head())
sarsa_df = rl.sarsa(num_episodes=200)
print(sarsa_df.head())
q_df = rl.q_learning(num_episodes=200)
print(q_df.head())
Download counts and popularity will appear here as the collector receives them.
| Version | Published | Direct dependencies | Open version |
|---|---|---|---|
| 1.1.0 | 23 May 2026 | 15 |
This describes our collected data; it is not a security assessment.
Observed since 20 Oct, 17:25 UTC
No superseded metadata states collected. Unchanged observations do not create new revisions.
package:cde6653bca7bfb48e3a8bf38a870f7ac3ddcc1e68e0abc334cd6c81049a1d2d1