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A simple stochastic OpenAI environment for training RL agents

Project description

This repository contains a PIP package which is an OpenAI environment for simulating an enironment in which bananas get sold.

Installation

Install the OpenAI gym.

Then install this package via

pip install -e .

Usage

import gym
import gym_banana

env = gym.make('Banana-v0')

See https://github.com/matthiasplappert/keras-rl/tree/master/examples for some examples.

The Environment

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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