Innovative edge caching: A multi-agent deep reinforcement learning approach for cooperative replacement strategies.
Zengwei LyuYu ZhangXiaohui YuanZhenchun WeiYu FuLin FengHaodong ZhouPublished in: Comput. Networks (2024)
Keyphrases
- multi agent
- cooperative
- reinforcement learning
- learning agents
- multi agent systems
- multi agent reinforcement learning
- agent cooperation
- multiagent reinforcement learning
- single agent
- proxy cache
- partially observable stochastic games
- function approximation
- intelligent agents
- edge detection
- query processing
- state space
- reinforcement learning agents
- edge information
- multiple agents
- control strategies
- multiagent systems
- multi agent environments
- software agents
- cooperating agents
- data access
- machine learning
- learning process
- model free
- weighted graph
- cooperative agents
- reinforcement learning algorithms
- edge detector
- game theory
- markov decision processes
- dynamic environments
- dynamic programming
- agent oriented
- stochastic games
- temporal difference
- online auctions
- exploration strategy
- autonomous agents
- input image
- learning algorithm