Simple functionality for the creation of visuals-based OpenAI Gym environments.
Project description
Gymmick
A library offering simple functionality for the creation of simple visuals-based OpenAI Gym environments.
Description
The purpose of this library is to create an easier way for users to make custom visual-based environments compatible with OpenAI Gym. Along with the basics of any Gym environment (ENV class and defining functions), the library will contain special functions to make state handling (for observation creation) easier as well as a predefined visualization tool which can be activated upon request (by changing a default argument when creating an environment instance). If the user does not want a visual/physics-based environment, they can opt to add their own variables to an optional argument dictionary when instantiating the class and have complete freedom with the manipulation of the values in said dictionary as the states of the environment change.
This library is not an advanced tool, but provides users freedom to do (almost) whatever they want in their environment. Flexibility for some environment functions is a priority and pending features include:
Functions for Collision Detection
Gravity for Members of the Environment
Visibility and "Tangibility" of Environment Members
Support for Irregular Polygons
Rotation of Environment Members
Installation
To install, simply use the command:
pip install gymmick
Usage
Import
from gymmick import creategym
from gymmick import members
Create an Environment
To create an environment, you must also have created a handler
function and know the details of the environment (action/observation space, episode length, using a screen, etc.). Here is the __init__()
function's parameters for the creategym.FreeSpaceEnv
class:
def __init__(self, action_space, observation_space, length, _handler, color = (0, 0, 0), scr=False, **kwargs)
Note: If you wish to be able to utilize the screen for the above class, then initialize the environment with scr=(<screen width>, <screen height>)
.
and here is the GridworldEnv.__init__()
parameters:
def __init__(self, action_space, observation_space, length, _handler, table_dim, color = (0, 0, 0), **kwargs)
Note: If you wish to be able to utilize the screen for the above class, then initialize the table_dim
parameter with ((<number of rows>, <row height>), (<number of columns>, <column width>))
. Both <number of rows>
and <number of columns>
must be at least 1. If <row height>
or <column width>
is 0, then the environment will not be instantiated with a screen, but the grid (and its variables) will still be accessible.
Here are examples of instantiating both environments, with handler functions, and other class parameters already in place:
def first(action):
prev = agent1.x
agent1.change_attr(x=agent1.x+(action-1))
done = False
if agent1.x == goal1.x:
reward = 1
done = True
elif (abs(agent1.x-goal1.x)<abs(prev-goal1.x)):
reward = 1
else:
reward = -1
observation = goal1.x-agent1.x
return observation, reward, done, {}
def second(action):
prev = agent2.col
agent2.change_attr(col = agent2.col+(action-1))
done = False
if agent2.col == goal2.col:
reward = 1
done = True
elif abs(agent2.col-goal2.col)<abs(prev-goal2.col):
reward = 1
else:
reward = -1
observation = goal2.col-agent2.col
return observation, reward, done, {}
action = spaces.Discrete(3)
observation1 = spaces.Box(low = np.array([-1500]), high = np.array([1500]))
observation2 = spaces.Box(low = np.array([-15]), high = np.array([15]))
env = FreeSpaceEnv(action, observation1, 1500, first, scr = (1000, 1000))
grid = GridworldEnv(action, observation2, 100, second, ((20, 25), (15, 37)))
Adding members to environments
To add members to environments, instantiate them from the gymmick.members
class with appropriate init parameters:
gymmick.members.FreeSpaceRect(<x>, <y>, <width>, <height>, <horizontal velocity>, <vertical velocity>, <mass>, <RGB color tuple>)
gymmick.members.CellRect(<row>, <column>, <horizontal velocity>, <vertical velocity>, <mass>, <RGB color tuple>)
gymmick.members.Circle(<x>, <y>, <radius>, <horizontal velocity>, <vertical velocity>, <mass>, <RGB color tuple>)
Note: Currently, the velocity parameter does not have any effect on the environment or object. Therefore, whatever vy
or vx
is instantiated is irrelevant, unless the user is using these variables in their own handler functions. Functionality for velocity is coming soon.
Note: FreeSpaceRect
and Circle
can only be used in the FreeSpaceEnv
environment, while CellRect
can only be used in the GridEnv
environment.
Note: CellRect
can have <row>
and <col>
values outside the bounds of its environment (they will just remain in a seperate array outside of the main table). Depending on how the user manipulates this object, it can switch its presence between GridEnv.table
and GridEnv.outside
.
Also, make sure to create a copy of the member variables so that they can be reset at the end of each episode. There will be future updates to the library in which users will not have to continuously re-add these members to the environment:
agent1_copy = FreeSpaceRect(0, 500, 50, 50, 0, 0, 0, (255, 0, 0))
agent2_copy = CellRect(10, 0, 0, 0, 0, (255, 0, 0))
goal1_copy = FreeSpaceRect(427, 500, 50, 50, 0, 0, 0, (0, 255, 0))
goal2_copy = CellRect(10, 11, 0, 0, 0, (0, 255, 0))
To add a member to the environt, use the environment's built-in method:
env.add_member(agent1)
env.add_member(goal1)
grid.add_member(agent2)
grid.add_member(goal2)
Run the environment
To run (and view) the grid
environment, run the following code:
for _ in range(<number of episodes>):
total_reward = 0
while True:
action = grid.action_space.sample()
obs, reward, done, info = grid.step(action)
total_reward += reward
grid.render()
if done == True:
break
print(total_reward)
grid.reset()
agent2 = agent2_copy
goal2 = goal2_copy
grid.add_member(agent2)
grid.add_member(goal2)
Similarly, you can run the env
environment by substituting its name for grid
in the above example.
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