Manurung, Auralius and Kristiana, Lisa and Uddin, Nur (2022) YADPF: A reusable deterministic dynamic programming implementation in MATLAB. SofwareX, 17 (101001). pp. 1-6.
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Abstract
This paper introduces the YADPF package, a collection of reusable MATLAB functions to solve deterministic discrete-time optimal control problems using a dynamic programming algorithm. For finite- and infinite-horizon optimal control problems, two types of dynamic programming algorithms are implemented: backward dynamic programming and value iteration. Like other implementations, users must provide the discretized state and input variables, the model dynamic equation, the terminal cost function, and the stage cost function. To more motivate users to use this MATLAB function package, we also provide more than ten academic case studies on how the YADPF function package can solve dynamic optimization problems with detailed step-by-step instructions. The provided guides and examples are expected to help users, especially, students and researchers initiate instant dynamic programming experiences with minimal coding expertise.
| Item Type: | Artikel |
|---|---|
| Uncontrolled Keywords: | Dynamic programming Optimal control Dynamic optimization Reinforcement learning |
| Subjects: | T Technology > T Technology (General) |
| Depositing User: | Admin Repository |
| Date Deposited: | 21 Jun 2022 08:03 |
| Last Modified: | 16 Jan 2023 02:02 |
| URI: | http://eprints.upj.ac.id/id/eprint/2686 |
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