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3. Multi agent reinforcement learning

2022-07-08 01:26:00 【C--G】

Basic concepts

Settings

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  • Fully Cooperative Setting
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  • Fully Competitive Setting
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  • Mixed Cooperative & Competitive
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  • Self-Interested Setting
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Basic terminology

  • State,Action,State Transition
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  • Rewards
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  • Returns
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  • Policy Network
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  • Uncertainty in the Return
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  • State-Value Function
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Convergence

  • Single-Agent Policy Learning
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  • Multi-Agent Policy Learning
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  • Difficulty of MARL
    Single-Agent Policy Gradient for MARL Insert picture description here
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Architectures

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Fully Decentralized

  • Execution
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  • Actor-Critic Method
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Fully Centralized

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  • Method
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  • Shortcoming：Slow during Execution
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Centralized Training with Decentralized Execution

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Parameter Sharing

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