Large-scale Machine Learning Cluster Scheduling via Multi-agent Graph Reinforcement Learning.
Xiaoyang ZhaoChuan WuPublished in: CoRR (2021)
Keyphrases
- reinforcement learning
- multi agent
- machine learning
- learning algorithm
- function approximation
- state space
- learning problems
- scheduling algorithm
- random walk
- graph representation
- small scale
- supervised learning
- temporal difference
- data clustering
- graph theory
- resource allocation
- graph structure
- proximity graph
- clustering algorithm
- massive graphs
- optimal policy
- weighted graph
- learning process
- model free
- scheduling problem
- active learning
- single agent
- directed acyclic graph
- graph mining
- bipartite graph
- nodes of a graph
- decision trees
- cooperative
- pattern recognition
- markov decision processes
- transfer learning
- data points
- information extraction
- multi agent environments
- dynamic programming
- reinforcement learning algorithms
- support vector machine
- learning tasks
- text mining
- machine learning methods
- graph matching
- hierarchical clustering
- response time
- multiple agents
- text classification
- machine learning algorithms
- cluster analysis
- partially observable markov decision processes
- learning agents
- multi agent reinforcement learning
- directed graph
- traffic signal control
- inductive logic programming