Titlebook: Reinforcement Learning for Sequential Decision and Optimal Control; Shengbo Eben Li Textbook 2023 The Editor(s) (if applicable) and The Au

ligature

Model-Free Indirect RL: Temporal Difference,e interdisciplinary fields of neuroscience and psychology. A few physiological studies have found similarities to TD learning, for example, the firing rate of dopamine neurons in the brain appears to be proportional to a reward difference between the estimated reward and the actual reward. The large

鎮(zhèn)壓

紅潤(rùn)

Indirect RL with Function Approximation,t of indirect RL. This architecture has two cyclic components: one is called actor, and the other is called critic. The actor controls how the agent behaves with respect to a learned policy, while the critic evaluates the agent’s behavior by estimating its value function. Although many successful ap

Nomadic

Direct RL with Policy Gradient,rect RL, however, especially with off-policy gradients, is the easiness of instability in the training process. The key idea to addressing this issue is to avoid adjusting the policy too fast at each step, and representative methods include trust region policy optimization (TRPO) and proximal policy

身體萌芽

Approximate Dynamic Programming, from Bellman’s principle. However, since the control policy must be approximated by a proper parameterized function, the selection of the parametric structure is strongly related to closed-loop optimality. For instance, a tracking problem has two kinds of policies: the first-point policy poses unne

interrogate

State Constraints and Safety Consideration,ic-scenery (ACS) is proposed to address the issue, whose elements include policy improvement (PIM), policy evaluation (PEV), and a newly added region identification (RID) step. By equipping an OCP with hard state constraint, the safety guarantee is equivalent to solving this constrained control task

衣服

Deep Reinforcement Learning,by certain tricks described in this chapter, for example, implementing constrained policy update and separated target network for higher training stability, while utilizing double Q-functions or distributional return function to eliminate overestimation.

adjacent

Fester

開(kāi)始從未

Shengbo Eben Li P?dagogik; sie wird ausgesprochen kontrovers, teilweise auch, insbesondere in ihren erkenntnistheoretischen Facetten, polemisch geführt. Die zun?chst in den USA geführte Diskussion hat l?ngst auch die deutsche Erkenntnistheorie, Psychologie, P?dagogik und in jüngster Zeit verst?rkt auch die Fachdid