Gradient Q$(σ, λ)$: A Unified Algorithm with Function Approximation for Reinforcement Learning

6 Sep 2019Long YangYu ZhangQian ZhengPengfei LiGang Pan

Full-sampling (e.g., Q-learning) and pure-expectation (e.g., Expected Sarsa) algorithms are efficient and frequently used techniques in reinforcement learning. Q$(\sigma,\lambda)$ is the first approach unifies them with eligibility trace through the sampling degree $\sigma$... (read more)

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