.png){kind=icon}
Return
Lebesgue-Sampling-Based Optimal Control Problems With Time Aggregation
.png){kind=icon}
PRE
AI
DOI：10.1109/TAC.2010.2073610.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
We formulate the Lebesgue-sampling-based optimal control problem. We show that the problem can be solved by the time aggregation approach in Markov decision processes (MDP) theory. Policy-iteration-based and reinforcement-learning-based methods are developed for the optimal policies. Both analytical solutions and sample-path-based algorithms are given. Compared to the periodic-sampling scheme, the Lebesgue sampling scheme improves system performance.
Keywords:
Aggregation
Markov decision processes (MDPs)
performance potentials
reinforcement learning
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
7
Papers:
1.3W
Citations:
6.7W
Organization
Cited Papers
.png){kind=icon}
Critical Evaluation and Thermodynamic Optimization of the Li2O-Al2O3 and Li2O-MgO-Al2O3 Systems
PREAI
ShareSaveShareSave
ShareSave
View more