What are the key differences between on-policy methods like SARSA and off-policy methods like Q-learning in the context of deep reinforcement learning?
Tuesday, 11 June 2024
by EITCA Academy
In the realm of deep reinforcement learning (DRL), the distinction between on-policy and off-policy methods is fundamental, particularly when considering algorithms such as SARSA (State-Action-Reward-State-Action) and Q-learning. These methods differ in their approach to learning and policy evaluation, which has significant implications for their performance and applicability in various environments. On-policy methods, such as SARSA,
- Published in Artificial Intelligence, EITC/AI/ARL Advanced Reinforcement Learning, Deep reinforcement learning, Function approximation and deep reinforcement learning, Examination review
Tagged under:
Artificial Intelligence, Off-Policy, On-Policy, Q-learning, Reinforcement Learning, SARSA