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multi-agent-learning
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Paper list of multi-agent reinforcement learning (MARL)
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Updated
Jan 24, 2021
A selection of state-of-the-art research materials on decision making and motion planning.
machine-learning
reinforcement-learning
deep-learning
algorithms
robotics
decision-making
motion-planning
artificial-intelligence
trajectory-generation
autonomous-vehicles
causal-inference
inverse-reinforcement-learning
intelligent-transportation-systems
trajectory-prediction
motion-control
multiagent-reinforcement-learning
multi-agent-learning
trajectory-planning
motion-prediction
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Aug 26, 2020
[NeurIPS2021] Learning Distilled Collaboration Graph for Multi-Agent Perception
computer-vision
deep-learning
graph
autonomous-driving
knowledge-distillation
communication-networks
v2v
collaborative-learning
multi-agent-learning
multi-agent-system
graph-learning
3d-object-detection
point-cloud-processing
v2x-communication
multi-agent-perception
3d-scene-understanding
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Updated
Feb 18, 2022 - Python
A curated list of multiagent learning and related area resources.
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Aug 15, 2019
A Collection of Multi-Agent Reinforcement Learning (MARL) Resources
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Dec 1, 2021
Multi-Agent Reinforcement Learning (MARL) papers
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Jun 5, 2021
Active visual tracking library based on PyTorch.
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Dec 17, 2021 - Python
We reproduced DeepMind's results and implement a meta-learning (MLSH) agent which can generalize across minigames.
reinforcement-learning
deep-reinforcement-learning
minigames
multi-agent-learning
starcraft2
starcraft2-ai
sc2le
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Updated
Mar 30, 2021 - Python
A curated list of awesome multi-agent learning papers
awesome
reinforcement-learning
communication
multi-agent
rl
awesome-list
imitation-learning
multi-agent-systems
inverse-reinforcement-learning
multi-agent-learning
multi-agent-reinforcement-learning
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Updated
Jan 10, 2022
Computing mixed-strategy Nash Equilibria for games involving multiple players
julia
game-theory
multi-agent-systems
nash-equilibrium
multi-agent-learning
multi-agent-reinforcement-learning
game-theory-algorithms
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Mar 4, 2022 - Julia
Multi agent reinforement learning. Chaser and runner.
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Updated
Jan 14, 2020 - Python
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Hi,
I am currently using your FinRL_PortfolioAllocation_NeurIPS_2020 code and I have some strange behavior at the beginning of training. Sometimes the first episode reward mean value is super high and then drops during the training as shown on the tensorboard plot. This high value is never reached again. Any idea why this is happening ?
Edit: I'm training PPO agent from stablebaselines3 wit