SSP-MMC
dymos
| SSP-MMC | dymos | |
|---|---|---|
| 8 | 4 | |
| 114 | 186 | |
| 0.0% | 0.5% | |
| 4.1 | 7.9 | |
| 5 months ago | 8 days ago | |
| Python | Python | |
| MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
SSP-MMC
- Main updates of FSRS4Anki from v3.7.0 to v3.23.0
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If I had a dollar for every Anki review...
FSRS is based on the DSR model proposed by Piotr Wozniak, the author of SuperMemo. FSRS is improved with the DHP model introduced in the paper: A Stochastic Shortest Path Algorithm for Optimizing Spaced Repetition Scheduling.
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I used FSRS Helper to reschedule my cards
free access: www.maimemo.com/paper/
- The next version of AnkiMobile will support FSRS4Anki!
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How to use the next-generation spaced repetition algorithm FSRS on Anki?
FSRS4Anki, aka Free Spaced Repetition Schedule for Anki, is based on the three-component model of memory proposed by Piotr Wozniak and the stochastic shortest path algorithm introduced in my paper. It makes great progress in memory prediction and scheduling optimization.
- GitHub - maimemo/SSP-MMC: A Stochastic Shortest Path Algorithm for Optimizing Spaced Repetition Scheduling
- A Stochastic Shortest Path Algorithm for Optimizing Spaced Repetition Scheduling | Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
dymos
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Optimal Control of a Formula 1 Car - Circuit de Barcelona-Catalunya
And the code here: https://github.com/OpenMDAO/dymos/tree/master/dymos/examples/racecar
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Dumb question but should I avoid putting the 'magic tyre formula' in my paper?
The paper (actually an 'individual report') is to discuss my contribution and results for a group project. The overall project is on improving our electric bike that take's part in the Isle of Man TT Zero, mostly by implementing battery and motor cooling systems. I've developed a fairly lightweight lap time simulator (using Dymos) that integrates transient models for the cooling system, allowing us to essentially simulate our cooling systems within the lap time simulator.
- How do I transform these complicated differential equations into more straightforward ones?
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Could someone help with the direction on an optimal control theory problem?
Referenced from one of the comments here: https://github.com/OpenMDAO/dymos/issues/369
What are some alternatives?
fsrs4anki - A modern Anki custom scheduling based on Free Spaced Repetition Scheduler algorithm
build_pyoptsparse - python script to build/install pyoptsparse with IPOPT (and optionally SNOPT)
Anki-Android - AnkiDroid: Anki flashcards on Android. Your secret trick to achieve superhuman information retention.
SpiceyPy - SpiceyPy: a Pythonic Wrapper for the SPICE Toolkit.
fsrs-optimizer - FSRS Optimizer Package
apod-api - Astronomy Picture of the Day API service
thoughts-memo - Thoughts Memo 小站
HJxB - Continuous-Time/State/Action Fitted Value Iteration via Hamilton-Jacobi-Bellman (HJB)
free-spaced-repetition-scheduler - A spaced repetition algorithm based on DSR model
robot - Functions and classes for gradient-based robot motion planning, written in Ivy.
anki_straight_reward - Escape Ease Hell!
robot - Functions and classes for gradient-based robot motion planning, written in Ivy. [Moved to: https://github.com/unifyai/robot]