Equilibrated and Fast Resources Allocation for Massive and Diversified MTC Services Using Multiagent Deep Reinforcement Learning.
Lun TangYucong DuQianbin ChenQinghai LiuJinyu LiShirui LiPublished in: IEEE Internet Things J. (2023)
Keyphrases
- multi agent
- reinforcement learning
- distributed resource allocation
- learning agents
- resource allocation
- multiagent learning
- allocate resources
- computing resources
- resource discovery
- information resources
- resource allocation problems
- multiagent systems
- information services
- multi agent systems
- grid environment
- function approximation
- heterogeneous environments
- state space
- resource utilization
- computing environments
- service providers
- resource management
- autonomous agents
- service oriented
- geographical information
- web services
- grid resource
- cooperative
- service discovery
- digital resources
- network resources
- resource constraints
- machine learning
- service composition
- end users
- temporal difference
- semantic interoperability
- computing infrastructure
- optimal policy
- personal preferences
- e learning
- reinforcement learning algorithms
- data analysis
- learning process
- distributed computing environment
- dynamic programming
- semantic web technologies
- exchange information
- stochastic games
- agent technology
- resource sharing
- limited resources