RLE-Foundation/RLeXplore

RLeXplore provides stable baselines of exploration methods in reinforcement learning, such as intrinsic curiosity module (ICM), random network distillation (RND) and rewarding impact-driven exploration (RIDE).

461 23 +0/wk

GitHub

baselines efficient-algorithm exploration-strategy gym machine-learning pybullet pytorch reinforcement-learning robotics toolbox

Trend 3

Star & Fork Trend (21 data points)

Stars

Forks

Multi-Source Signals

GitHub

stars 461

forks 23

Growth Velocity

RLE-Foundation/RLeXplore has +0 stars this period . 7-day velocity: 0.4%.

Deep analysis is being generated for this repository.

Signal-backed technical analysis will be available soon.

Metric	RLeXplore	DreamServer	automlbenchmark	CortexON
Stars	461	459	459	458
Forks	23	129	147	77
Weekly Growth	+0	+0	+0	+0
Language	Jupyter Notebook	Rust	Python	Python
Sources	1	1	1	1
License	MIT	Apache-2.0	MIT	NOASSERTION

Capability Radar vs DreamServer

RLeXplore

DreamServer

Maintenance Activity 0

Last code push 370 days ago.

Community Engagement 70

Fork-to-star ratio: 5.0%. Lower fork ratio may indicate passive usage.

Issue Burden 70

Issue data not yet available.

Growth Momentum 30

No measurable growth in the current period (first-day cold start expected).

License Clarity 95

Licensed under MIT. Permissive — safe for commercial use.

Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.