# MemTensor/MemRL

<https://repo.masters-masters.com/en/repos/MemTensor/MemRL>

[Home](https://repo.masters-masters.com/en) › [MemTensor](https://repo.masters-masters.com/en/owners/MemTensor) › [MemRL](https://repo.masters-masters.com/en/repos/MemTensor/MemRL)

MemTensor/MemRL has 194 stars on GitHub. Its RepoMasters card: Prototype tier. Paper: “MEMRL: SELF-EVOLVING AGENTS VIA RUNTIME REINFORCEMENT LEARNING ON…

| Field | Value |
| --- | --- |
| Owner | [MemTensor](https://repo.masters-masters.com/en/owners/MemTensor) |
| Stars | 194 |
| Forks | 18 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | MIT |
| Created | 2026 |
| Tier | [Prototype (100 to 249 ★)](https://repo.masters-masters.com/en/ranks/rush) |
| View on GitHub | [MemTensor/MemRL](https://github.com/MemTensor/MemRL) |

## Repository

Paper: “MEMRL: SELF-EVOLVING AGENTS VIA RUNTIME REINFORCEMENT LEARNING ON EPISODIC MEMORY” Open-Source Code

The tier for repos with 100 to 249 ★. Published odds per card pulled: 70%. Rarity: Common.

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Data: GitHub · Illustration drawn by RepoMasters from the repo’s ID and its language color.