Natural Policy Gradients In Reinforcement Learning Explained.
Wouter J. A. van HeeswijkPublished in: CoRR (2022)
Keyphrases
- reinforcement learning
- optimal policy
- policy search
- markov decision process
- action selection
- reinforcement learning problems
- reinforcement learning algorithms
- policy iteration
- function approximation
- partially observable environments
- state space
- action space
- reward function
- markov decision processes
- partially observable
- actor critic
- state and action spaces
- markov decision problems
- control policies
- approximate dynamic programming
- policy evaluation
- policy gradient
- partially observable markov decision processes
- model free
- decision problems
- multi agent
- function approximators
- control policy
- state action
- partially observable domains
- real world
- average cost
- temporal difference
- machine learning
- neural network
- rl algorithms
- temporal difference learning
- state dependent
- continuous state
- control problems
- man made
- partially observable markov decision process
- optimal control
- learning problems
- agent learns
- supervised learning
- model free reinforcement learning