A pytorch implementation of Structured Exploration via Deep Hierarchical Coordination
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Updated
Aug 18, 2017 - Python
A pytorch implementation of Structured Exploration via Deep Hierarchical Coordination
Learning Grounded Language via Split Screen Communication Learning via Deep Multi-Agent Reinforcement Learning
references: https://github.com/ankonzoid/Deep-Reinforcement-Learning-Tutorials/tree/master/hunterprey
Implementation of Q-Learning using TD error to navigate a maze avoiding obstacles and a moving enemy
Slither-in Inspired Snake Environment for OpenAI Gym (Part of Requests for Research 2.0)
Multi Agent extension of the PyGame Learning Environment (MAPLE)
Small collection of Multi-agent gym environments.
A pytorch implementation of MADDPG (multi-agent deep deterministic policy gradient)
A multi agent re-enforcement learning environment for many on many bot fights between space ships
Board-and-card games are those which involve higher level of uncertainty as it includes the probability of getting the right card and the moves made by other players. We look to model such games as Markov Games and find an optimal policy through the Minimax – Q algorithm. This will also be a test for the Minimax – Q algorithm to check how it per…
This is Multi agent deep reinforcement learning repo which trains an agent to play Tennis. It trains by playing against itself.
Implementation of the DDPG algorithm to solve Continuous Control Reacher Environment
Third-degree Computer Engineering subject at Universitat de Barcelona
Multi-Agent Reinforcement Learning Environment
Resource Abstraction (AAMAS 2016)
The Reinforcement-Learning-Related Papers of ICLR 2019
Implementation of Multi-Agent Reinforcement Learning algorithm(s). Currently includes: MADDPG
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