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hardwareentity · one source so far

reinforcement learning

for robotics hobbyists

Steadygithub
Signal score
3
Live items
1
Trajectory
Steady
7-day est. ~3

Why this scored 3

every term, weighted
Velocity+7.3 / 40

Its fastest-moving item, measured against the pace of its own source

Acceleration+12.5 / 25

Whether that velocity is itself speeding up, as a per-hour rate

Cross-source spread+0.0 / 25

How many independent communities its own items come from

Recency+0.0 / 10

Decays to zero over 14 days, counted from when we first saw it

Saturation penalty17.1 / 30

Subtracted once something is big and old — sized by its biggest item, aged from when we first saw it

Composite2.6

Weights are hand-tuned, not learned — we're calibrating them against realized trends as history accumulates. On an entity's first sighting there's no previous reading to compare against, so acceleration starts from a neutral prior rather than a measurement, and velocity falls back to engagement over its whole lifetime until a second reading exists. Full methodology

Outlook

low confidence · estimate, not a guarantee

7-day

~3

range 015

14-day

~0

range 015

30-day

~0

range 019

Signal history

7-day window (free)
023

projected trajectory (estimate, not a guarantee)

The evidence

The live items this entity's score aggregates — every community independently talking about it right now. This is the corroboration, shown, not claimed.

  1. 1
    46

    Knowledge- and Gradient-Guided Reinforcement Learning for Parametrized Action Markov Decision Processes

    Improves decision processes · for ai decision makers

    arxivSteadyai58d ago
  2. 2
    31

    Searching for New Physics with Reinforcement Learning

    Applies reinforcement learning to explore parameter spaces for potential new physics. · for research scientists, ml physicists

    arxivSteady 2 · reinforcement learningscience1d ago
  3. 3
    19

    Stochastic Dynamics on Persistence Diagram Space via Reinforcement Learning

    Learning via stochastic dynamics · for ai researchers

    arxivSteadyai35d ago
  4. 4
    17

    Microduck-build-tutorial — A practical hardware and software setup for a compact RL-powered biped robot.

    Tutorial details building a compact RL-powered biped robot with readily available components. · for robotics hobbyists

    githubSteadyhardware8 saturated2d ago
  5. 5
    9

    Evaluating Fuzz Testing for Reinforcement Learning Agents

    Fuzz testing for RL agents · for ai devs

    arxivSteadyai45d ago
  6. 6
    7

    When Model Merging Rivals Joint Multi-Task Reinforcement Learning: A Task-Vector Geometry Analysis

    Improves joint task learning · for ai researchers

    arxivSteadyai53d ago
  7. 7
    7

    PATS: Policy-Aware Training Scaffolding for Agentic Reinforcement Learning

    Improves reinforcement learning · for ai researchers

    arxivSteadyai49d ago