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Coordinated Reinforcement Learning in Multi-Path Routing

Coordinated Reinforcement Learning in Multi-Path Routing. Rong Zhou. Multi-Path Routing & Reinforcement Learning. Multi-path routing finds all paths between a sender and a receiver has several advantages: better bandwidth utilization, minimizing delay, improved fault tolerance

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Coordinated Reinforcement Learning in Multi-Path Routing

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  1. Coordinated Reinforcement Learning in Multi-Path Routing Rong Zhou

  2. Multi-Path Routing & Reinforcement Learning • Multi-path routing • finds all paths between a sender and a receiver • has several advantages: better bandwidth utilization, minimizing delay, improved fault tolerance • Reinforcement learning • Feedback is evaluative • Framework for multi-path routing • Exploitation vs. exploration in multi-path routing • Regular ants • Uniform ants

  3. Proposed Approach • Problems with regular and uniform ants • Lack of multi-agent coordination • Hybrid ants • combine the traits of two types of ants • have built-in multi-agent coordination mechanism • Experimental evaluation • Link-state routing • Hybrid-ant routing

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