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08of22 - Decentralized Reinforcement Learning For The Online Optimization of Distributed Systems by Júlio Gallinaro Maranho is a document available to read on EtoBox.
What is 08of22 - Decentralized Reinforcement Learning For The Online Optimization of Distributed Systems about?
This document provides an overview of decentralized reinforcement learning (DRL) for optimizing distributed systems, emphasizing the challenges and complexities involved in multi-agent environments. It discusses the necessity for cooperation among agents to improve global utility, the impact of network dynamics on learning algorithms, and the formulation of DRL problems in terms of stochastic control. The authors also highlight existing approaches and propose a model for collaborative reinforcement learning
- Author
- Júlio Gallinaro Maranho
- Language
- EN