Understanding Reinforcement Learning Algorithms: The Progress from Basic Q-learning to Proximal Policy Optimization.
Mohamed-Amine ChadiHajar MousannifPublished in: CoRR (2023)
Keyphrases
- reinforcement learning algorithms
- reinforcement learning problems
- reinforcement learning
- policy search
- reward function
- markov decision processes
- model free
- partially observable environments
- state space
- optimal policy
- eligibility traces
- actor critic
- reinforcement learning methods
- markov games
- policy gradient
- temporal difference
- function approximation
- learning algorithm
- function approximators
- policy iteration
- temporal difference learning
- action selection
- markov decision process
- dynamic programming
- td learning
- solving problems
- support vector machine svm
- monte carlo
- reward shaping
- multiagent reinforcement learning
- search space
- partially observable
- markov decision problems
- stochastic games
- learning agent