Interpretable Reinforcement Learning via Differentiable Decision Trees.
Ivan Dario Jimenez RodriguezTaylor W. KillianSung-Hyun SonMatthew C. GombolayPublished in: CoRR (2019)
Keyphrases
- decision trees
- reinforcement learning
- classification rules
- machine learning
- decision tree induction
- predictive accuracy
- reinforcement learning algorithms
- function approximation
- optimal policy
- temporal difference
- state space
- optimal control
- rule induction
- loss function
- naive bayes
- random forest
- training data
- markov decision processes
- model free
- decision tree algorithm
- data mining methods
- rule sets
- multi agent reinforcement learning
- decision rules
- machine learning algorithms
- learning algorithm
- objective function
- training set
- neural network
- decision tree classifiers
- decision tree learning
- temporal difference learning
- constructive induction
- data sets
- learning process
- least squares
- logistic regression
- transfer learning
- regression trees
- hidden markov models
- attribute selection
- genetic algorithm
- genetic programming
- base classifiers