Late Breaking Results: Reinforcement Learning for Scalable Logic Optimization with Graph Neural Networks.
Xavier TimonedaLukas CavigelliPublished in: DAC (2021)
Keyphrases
- neural network
- reinforcement learning
- function approximation
- graph structure
- optimization problems
- pattern recognition
- random walk
- optimization algorithm
- optimization method
- markov decision processes
- genetic algorithm
- optimization process
- directed graph
- connected components
- structured data
- multi valued
- artificial neural networks
- model free
- graph theoretic
- learning classifier systems
- graph mining
- graph theory
- highly non linear
- modal logic
- feed forward
- global optimization
- optimal policy
- learning algorithm
- neural nets
- bipartite graph
- graph matching
- neural network model
- graph representation
- sufficient conditions
- learning capabilities
- particle swarm optimization
- function approximators