Metadata-Version: 2.1
Name: barl
Version: 0.0.0.5
Summary: Bayesian Approximate Reinforcement Learning (BARL)
Home-page: https://github.com/ai-nikolai/barl
Author: nikolai rozanov
Author-email: nikolai.rozanov@gmail.com
License: Apache 2.0
Description: # BARL - Bayesian Approximate Reinforcement Learning
        This package should serve as a collection of tools to do RL in general and in particular bayesian RL.
        
        ## The Main Features(Jul 2019):
        1. estimators
        2. agents
        3. environments
        4. simulations & visualisation
        
        ## Installation:
        
        ### PIP:
        ```bash
        pip3 install barl
        ```
        
        ### Github:
        ```bash
        git clone https://github.com/ai-nikolai/barl
        cd barl
        pip3 install -e .
        ```
        
        ## Usage:
        
        ### Testing
        ```bash
        cd barl
        pytest
        ```
        
        ### Experiments:
        ```bash
        cd barl
        cd experiments
        python3 experiments_mab.py
        ```
        
        ### Scripts:
        ```python
        import barl
        
        env = barl.environments.MultiArmedBandit(arms=4)
        
        agent1 = barl.agents.baselines.RandomActionsSampler(numActions=4)
        
        total, arlist, _ = barl.simulations.run_state_less_agent_and_env( environment=env, agent=agent1, N=100)
        
        barl.utils.plotting.plot_reward_over_time_from_ar(arlist)
        ```
        
        
        
        ## Copyright (C) - Nikolai Rozanov 2019-Present
        
Platform: UNKNOWN
Requires-Python: >=3.6
Description-Content-Type: text/markdown
