Distributed Optimization, Game and Learning Algorithms Theory and Applications in Smart Grid Systems
This book provides the fundamental theory of distributed optimization, game and learning. It includes those working directly in optimization,-and also many other issues like time-varying topology, communication delay, equality or inequality constraints,-and random projections. This book is meant for...
| Main Authors: | , , |
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| Format: | eBook |
| Language: | English |
| Published: |
Singapore
Springer Nature Singapore
2021, 2021
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| Edition: | 1st ed. 2021 |
| Subjects: | |
| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- Cooperative Distributed Optimization in Multiagent Networks with Delays
- Constrained Consensus of Multi-Agent Systems with Time-Varying Topology
- Distributed Optimization under Inequality Constraints and Random Projections
- Accelerated Distributed Optimization over Digraphs with Stochastic Matrices
- Linear Convergence for Constrained Optimization over Time-Varying Digraphs
- Stochastic Gradient-Push for Economic Dispatch on Time-Varying Digraphs
- Reinforcement Learning in Energy Trading Game Among Smart Microgrids
- Reinforcement Learning for Constrained Games with Incomplete Information
- Reinforcement Learning for PHEV Route Choice based on Congestion Game