Webbwork on hindsight (Andrychowicz et al.,2024;Karkus et al.,2016). In that case, it is possible to evaluate a trajectory obtained while trying to achieve an original goal g0for an alternative goal g. Using importance sampling, this information can be exploited using the following central result. Theorem 4.1 (Every-decision hindsight policy gradient). Webb10 mars 2024 · It is proposed that it is not the sparsity of the reward itself that causes difficulty in credit assignment, but rather the information sparsity, which is then used to characterize when credit assignment is an obstacle to ef ficient learning. How do we formalize the challenge of credit assignment in reinforcement learning? Common …
Counterfactual Credit Assignment in Model-Free Reinforcement Learning
WebbIn order to efficiently and meaningfully utilize new data, we propose to explicitly assign credit to past decisions based on the likelihood of them having led to the observed outcome. This approach uses new information in … Webb1、为了解决long-term credit assignment问题，即智能体只能到某个游戏关卡结束以后才能获得实质性的奖励值，其他时候的奖励都是零，从而导致智能体无法认识到某个状态 … エタノール 泡
[2212.11636] Towards Causal Credit Assignment
WebbWe show that the family of hindsight credit assignment algorithms of Harutyunyan et al. (2024) can be derived using a combination of importance sampling and the conditional Monte Carlo method (Hammersley, 1956; Bratley et al., 1987). This new perspective suggests a new interpretation for HCA as a class of off-policy WebbIn order to efficiently and meaningfully utilize new data, we propose to explicitly assign credit to past decisions based on the likelihood of them having led to the observed … Webbas Hindsight Credit Assignment (HCA). The remainder of this section formalizes the insight outlined above, and derives the usual value functions and policy gradients in … エタノール 泡消火