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Integrating guidance into relational reinforcement learning
K Driessens
*
, S Dzeroski
*
Corresponding author for this work
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Keyphrases
Relational Reinforcement Learning
100%
Q-learning
100%
Q-function
66%
State Space
33%
Reinforcement Learning
33%
Decision Tree
33%
Tabular Form
33%
Relational Domain
33%
Sparse Reward
33%
Random Exploration
33%
Large State Space
33%
Structural Domains
33%
Neural Nets
33%
First Problem
33%
Engineering
Relational
100%
Reinforcement Learning
100%
Tabular Form
20%
Major Problem
20%
Structural Domain
20%
INIS
learning
100%
policy
33%
space
22%
solutions
11%
randomness
11%
exploration
11%
supply
11%
tables
11%
neural networks
11%
decision tree analysis
11%
Computer Science
Reinforcement Learning
100%
Neural Network
25%
Decision Trees
25%
State Space
25%
Large State Space
25%
Chemical Engineering
Reinforcement Learning
100%
Neural Network
25%