不安
发表于 2025-3-25 07:16:09
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ETCH
发表于 2025-3-25 09:19:31
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giggle
发表于 2025-3-25 14:12:07
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Incorporate
发表于 2025-3-25 18:30:00
ℓ1-Penalized Projected Bellman Residualeast-Squares Temporal Difference (LSTD) algorithm with ℓ.-regularization, which has proven to be effective in the supervised learning community. This has been done recently whit the LARS-TD algorithm, which replaces the projection operator of LSTD with an ℓ.-penalized projection and solves the corre
FELON
发表于 2025-3-25 23:06:09
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卡死偷电
发表于 2025-3-26 02:24:04
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上下倒置
发表于 2025-3-26 04:30:37
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Diaphragm
发表于 2025-3-26 10:37:26
Automatic Construction of Temporally Extended Actions for MDPs Using Bisimulation Metricsucting such actions, expressed as options , in a finite Markov Decision Process (MDP). To do this, we compute a bisimulation metric between the states in a small MDP and the states in a large MDP, which we want to solve. The . of this metric is then used to completely define a set of options
东西
发表于 2025-3-26 15:28:49
Unified Inter and Intra Options Learning Using Policy Gradient Methodsge into AI systems. The options framework, as introduced in Sutton, Precup and Singh (1999), provides a natural way to incorporate macro-actions into reinforcement learning. In the subgoals approach, learning is divided into two phases, first learning each option with a prescribed subgoal, and then
BRAWL
发表于 2025-3-26 18:04:59
Options with Exceptionsded actions thus allowing us to reuse that solution in solving larger problems. Often, it is hard to find subproblems that are exactly the same. These differences, however small, need to be accounted for in the reused policy. In this paper, the notion of options with exceptions is introduced to addr