General-purpose library for extracting interpretable models from Multi-Agent Reinforcement Learning systems
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Updated
May 10, 2020 - C++
General-purpose library for extracting interpretable models from Multi-Agent Reinforcement Learning systems
Model agnostic ML tooling for MOOS-IvP
This repository contains code for simulating coupled motion of rigid ball and fluid in 2D and this is used as an environment in Gym to train a controller to balance the ball in air.
Reinforcement learning algorithms
Reinforcement Learning agent for 2048 game
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