FinRL: Financial Reinforcement Learning.
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Updated
Mar 28, 2023 - Jupyter Notebook
FinRL: Financial Reinforcement Learning.
Paper list of multi-agent reinforcement learning (MARL)
A selection of state-of-the-art research materials on decision making and motion planning.
VMAS is a vectorized framework designed for efficient Multi-Agent Reinforcement Learning benchmarking. It is comprised of a vectorized 2D physics engine written in PyTorch and a set of challenging multi-robot scenarios. Additional scenarios can be implemented through a simple and modular interface.
[NeurIPS2021] Learning Distilled Collaboration Graph for Multi-Agent Perception
A Collection of Multi-Agent Reinforcement Learning (MARL) Resources
Multi-Agent Reinforcement Learning (MARL) papers
SDK for multi-agent collaborative perception.
A curated list of multiagent learning and related area resources.
Active visual tracking library based on PyTorch.
We reproduced DeepMind's results and implement a meta-learning (MLSH) agent which can generalize across minigames.
A curated list of awesome multi-agent learning papers
Computing mixed-strategy Nash Equilibria for games involving multiple players
Multi agent reinforement learning. Chaser and runner.
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