A simple stochastic OpenAI environment for training RL agents
This repository contains a PIP package which is an OpenAI environment for simulating an enironment in which bananas get sold.
Install the OpenAI gym.
Then install this package via
pip install -e .
import gym import gym_banana env = gym.make('Banana-v0')
See https://github.com/matthiasplappert/keras-rl/tree/master/examples for some examples.
Imagine you are selling bananas. One at a time. And the bananas get bad pretty quickly. Let's say in 3 days. The probability that I will sell the banana is given by
$$p(x) = (1+e)/(1. + e^(x+1))$$
where x-1 is my profit. This x-1 is my reward. If I don't sell the banana, the agent gets a reward of -1 (the price of the banana).
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