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Reinforcement Learning API made simple - FAST_RLAPI

fastrlapi is a high level reinforcement learning api focusing on ease of use and simplicity. Written in Python and running on top of established reinforcement learning libraries like tf-Agents, tensorforce or keras-rl.

Examples


from fastrlapi.agents import PpoAgent
from fastrlapi.callbacks import plot

ppoAgent = PpoAgent('CartPole-v0')
ppoAgent.train([plot.State(), plot.Loss(), plot.Rewards()])

More Detailed

from fastrlapi.agents import PpoAgent
from fastrlapi.callbacks import plot

ppoAgent = PpoAgent( 'Orso-v1',fc_layers=(500,500,500))
ppoAgent.train([plot.State(), plot.Loss(), plot.Rewards(), plot.Actions(), 
                plot.StepRewards(), plot.Steps(), plot.ToMovie()], 
                learning_rate = 0.0001, num_iterations = 500, max_steps_per_episode=50 )

Available Algorithms and Backends


algorithm tf-Agents tensorforce keras-rl (suspended) fastrlapi class name
CEM not available not available yes CemAgent
Dqn yes yes yes DqnAgent
Double Dqn open not available yes DoubleDqnAgent
Dueling Dqn not available yes yes DuelingDqnAgent
Ppo yes yes not available PpoAgent
Random yes yes not available RandomAgent
REINFORCE yes yes not available ReinforceAgent
SAC preview not available not available SacAgent

Installation


Install from pypi using pip:

pip install fastrlapi

Metadata

Release files for fastrlapi 0.0.1

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