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@@ -10,13 +10,13 @@ pinned: false
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  license: other
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  short_description: NEO alerting-satellite jitter reduction-Starship-style
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  ---
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- # Rendered Frame Theory (RFT) — Agent Console
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  I built this Space to be completely open about what I’ve made, how it works, and where it succeeds or fails.
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- Rendered Frame Theory (RFT) is a framework I developed independently to solve a recurring problem I kept encountering in real predictive systems: most pipelines wait too long to act. They chase certainty, then react. By the time a correction happens, energy has already been wasted, instability has already grown, or the system has already triggered false positives.
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- RFT flips the priority. It treats timing, uncertainty, and decision “collapse” as first-class variables instead of side effects.
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  This Space hosts working agents built using that approach. Nothing here is hidden. All code runs. All assumptions are stated. Results are shown honestly, including where the approach does not outperform conventional methods.
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@@ -34,9 +34,9 @@ Most systems do:
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  - correct once confidence is high
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  RFT changes the order of importance:
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- - predict state and delay
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  - estimate uncertainty explicitly
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- - collapse actions earlier when the cost of waiting is higher than the cost of acting
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  In practice, this can lead to:
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  - earlier meaningful corrections
@@ -44,6 +44,8 @@ In practice, this can lead to:
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  - lower compute/actuation usage
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  - more stable behaviour under noise
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  ---
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  ## What this Space is NOT
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  ## What’s inside
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  This Space includes:
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- - Near-Earth Object (NEO) alerting agent
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- - Satellite jitter reduction agent
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  - Starship-style re-entry & precision landing harness (simplified)
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  - A Benchmarks tab with baseline vs RFT runs using the same seed
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  - A Theory → Practice page mapping ideas directly to code behaviour
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- - A Mathematics tab defining what the variables mean (with units) and how they map into implementation
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- - An Investor / Agency walkthrough tab that explains what’s proven here and what’s needed next for production
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  Every agent:
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- - runs locally inside the Space
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  - shows plots
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  - exports CSV logs
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  - uses reproducible seeds
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  ## Why I’m making this open
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- I’m done hiding behind documents.
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- If this is “just clever coding”, that will be obvious once people run it.
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- If it isn’t, that will also be obvious.
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- Either way: the code speaks louder than claims.
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  Run it. Change parameters. Break it. Compare it.
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- That’s the standard I’m holding myself to.
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- Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 
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  license: other
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  short_description: NEO alerting-satellite jitter reduction-Starship-style
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  ---
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+ # Rendered Frame Theory (RFT) — Observer Agent Console
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  I built this Space to be completely open about what I’ve made, how it works, and where it succeeds or fails.
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+ Rendered Frame Theory (RFT) is a framework I developed independently to solve a recurring problem I kept encountering in real predictive systems: many pipelines wait too long to act. They chase certainty, then react. By the time a correction happens, energy has already been wasted, instability has already grown, or the system has already triggered false positives.
18
 
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+ RFT flips the priority. It treats timing, uncertainty, and decision “commit(what I call collapse) as first-class variables instead of side effects.
20
 
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  This Space hosts working agents built using that approach. Nothing here is hidden. All code runs. All assumptions are stated. Results are shown honestly, including where the approach does not outperform conventional methods.
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  - correct once confidence is high
35
 
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  RFT changes the order of importance:
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+ - predict state *and* delay cost
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  - estimate uncertainty explicitly
39
+ - commit actions earlier when the cost of waiting is higher than the cost of acting
40
 
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  In practice, this can lead to:
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  - earlier meaningful corrections
 
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  - lower compute/actuation usage
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  - more stable behaviour under noise
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+ **Important wording note:** when I use “observer” in this Space, I mean an explicit decision mechanism (uncertainty → τ_eff → gate → commit/wait). I am not making a claim of machine consciousness here.
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+
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  ---
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  ## What this Space is NOT
 
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  ## What’s inside
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  This Space includes:
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+ - Near-Earth Object (NEO) observer agent (noisy alert filtering)
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+ - Satellite jitter observer agent (duty reduction / chatter control)
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  - Starship-style re-entry & precision landing harness (simplified)
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  - A Benchmarks tab with baseline vs RFT runs using the same seed
70
  - A Theory → Practice page mapping ideas directly to code behaviour
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+ - A Mathematics tab defining what the variables mean and how they map into implementation
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+ - An Investor / Agency walkthrough tab explaining what’s demonstrated here and what would be needed next for production
73
 
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  Every agent:
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+ - runs inside the Space
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  - shows plots
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  - exports CSV logs
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  - uses reproducible seeds
 
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  ## Why I’m making this open
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+ I’m choosing transparency over hype.
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+ If this is “just clever coding”, that will be obvious once people run it. If it isn’t, that will also be obvious.
 
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+ Either way, the code and logs speak louder than claims.
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  Run it. Change parameters. Break it. Compare it.
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+ (Spaces config reference: https://huggingface.co/docs/hub/spaces-config-reference)