Deep reinforcement learning meets graph neural networks: Exploring a routing optimization use case.
Paul AlmasanJosé Suárez-VarelaKrzysztof RusekPere Barlet-RosAlbert Cabellos-AparicioPublished in: Comput. Commun. (2022)
Keyphrases
- neural network
- reinforcement learning
- optimization algorithm
- pattern recognition
- optimization problems
- graph theory
- random walk
- logistics distribution
- optimization method
- function approximators
- graph representation
- learning capabilities
- feed forward
- bipartite graph
- graph databases
- graph model
- graph mining
- fuzzy systems
- highly non linear
- function approximation
- multi layer
- graph structure
- neural network model
- connected components
- fuzzy logic
- learning algorithm
- genetic algorithm
- weighted graph
- radial basis function
- directed graph
- network architecture
- routing problem
- learning classifier systems
- dynamic programming
- artificial neural networks