Comments (7)
Hi @indhra007 .
Indeed it is totally possible to train two independant agents with DQN algorithm. All you have to do is to :
- Instantiate your OpenAI Gym like environment and get observation and action space for both agents (if they have different observation and/or action space)
import marl
from marl.agent import DQNAgent
env = my_env()
# This part may depend of the implementation of the environment
obs_space1 = env.observation_space[0]
act_space1 = env.action_space[0]
obs_space2 = env.observation_space[1]
act_space2 = env.action_space[1]
- Instantiate two DQNAgent with the best training parameters for each. Easiest way to do (with neither custom parameters nor custom model) is as follow:
agent1 = DQNAgent("MlpNet", obs_space1, act_space1)
print("#> Agent 1 :\n", agent1, "\n")
agent2 = DQNAgent("MlpNet", obs_space2, act_space2)
print("#> Agent 2 :\n", agent2, "\n")
- Instantiate your multi-agent system for reinforcement learning. If the agents are independant learners, you don't need to use
set_mas()
function because it means that they don't need to know local information about other agents (i.e. policies of other agents):
mas = MARL(agents_list=[agent1, agent2])
- Train and test your system
# Train the agent for 100 000 timesteps
mas.learn(env, nb_timesteps=100000)
# Test the agent for 10 episodes
mas.test(env, nb_episodes=10)
I hope this will help you. I continue to implement some module for this API and I hope I will have time
to improve the documentation in order to provide more usefull examples.
from marl.
@indhra007 sorry for the late answer. In order to avoid problems of importing packages when using notebook, go to the marl directory before installing it.
If you are using a Notebook or Google Colab, the following lines should fix the problem:
!git clone https://github.com/blavad/marl.git
%cd marl
!pip install -e .
or
!git clone https://github.com/blavad/marl.git
!cd marl
!pip install -e .
If you are using command line, something as follow should work:
git clone https://github.com/blavad/marl.git
cd marl
pip install -e .
from marl.
its kind of competitive between agent A vs agent B of same environment
from marl.
@blavad thanks for quick reply
If possible can u share an environment which has multi agents-with some documentation
from marl.
@blavad Any multi agent environment other than soccer,
Because of no soccer documentation it is not possible to understand
from marl.
@indhra007 For the moment I cannot share another well documented environment. I am currently working with another environment (for the game Hanabi) but it is not online yet.
You can check to this section of the documentation (https://blavad.github.io/marl/html/quickstart/environment.html) for a brief review of how to build an adequate environment.
I will let you know as soon as I make a repo with some multi-agent environments.
from marl.
Ok
Does the soccer environment works?
from marl.
Related Issues (3)
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from marl.