AGI Stream

Modular AGI Framework — User Guide

This guide will help to understand the input control and how they affect the system’s behavior over time.

1. Inputs — What You Control

Input	What It Is	How It Affects the System	Suggested Range
Stimulation Intensity (Slider)	Overall strength of input signals	Higher values increase system’s feedback and growth rate	0 (low) to 100 (high)
x	Symbolic base value	Used to calculate symbolic change (delta)	Typically 0.5 to 2.0
x′ (x prime)	Symbolic reference value	Compared with x to find system tension (delta)	Typically 0.5 to 3.0
M	Mental field input (component M)	Part of cognitive energy calculation	0 to 1
T	Mental field input (component T)	Part of cognitive energy calculation	0 to 1
F	Mental field input (component F)	Part of cognitive energy calculation	0 to 1

Note: The mental field inputs M, T, and F should ideally sum close to 1 to keep balanced energy weighting.

2. Outputs — What to Watch

Output	Meaning	What It Tells You
Quantum Reasoning Output	Instant feedback from input signals	Higher values mean stronger internal signals
Updated Recursive State	Current "energy" or knowledge level of system	Tracks growth or shrinkage over time
Symbolic Delta (Δ)	Measure of symbolic change/tension	Negative or positive values indicate system shift
Collapse Status	System condition: Stable, Collapse, or Diverge	Indicates if system is steady, simplifying, or exploding
Mental Field Energy	Weighted sum of mental inputs	Reflects cognitive bias or focus
Supervisor Decision	Continue or Adjust	Whether system suggests keeping course or changing
Octinary Logic Output	Symbolic internal state from fixed logic	Useful for debugging or symbolic tracking

3. How to Use — Practical Tips

• Start with moderate values:

  • Slider at 20–40%

  • x near 1.0, x′ slightly larger (1.2 to 1.5)

  • Mental inputs evenly split (e.g., M=0.33, T=0.33, F=0.34)

• Increase stimulation intensity to encourage growth or exploration.

• Watch the Recursive State:

  • If it grows exponentially and "Collapse Status" says “Diverge,” consider lowering stimulation or adjusting x/x′.

  • If it stabilizes or "Collapse" is triggered, the system is simplifying or pausing growth.

• Adjust x and x′ to influence symbolic delta:

  • Small delta values near zero promote stability.

  • Larger positive or negative delta values induce system shifts or bifurcations.

• Balance mental inputs (M, T, F) to guide system focus:

  • Increasing one input weights the system’s attention toward that component.

  • Uneven weights may cause bias or specialized behavior.

• Use the Supervisor Decision as a guide:

  • “Continue” means system is functioning within desired bounds.

  • “Adjust” suggests input changes are needed for system health.

4. Monitoring and Proactive Control

• Use the slider to modulate input intensity gradually rather than sudden jumps — this helps the system adapt smoothly.

• Observe the memory log for patterns:

  • Consistent divergence means inputs may be too aggressive.

  • Frequent collapse signals system may be over-constrained.

• Make changes before system diverges out of control to maintain stability.

• Experiment with inputs over time to see how the system evolves — this builds intuition about its behavior.

5. Reset and Restart

• Use the Clear Memory Log button to reset the system state and start fresh.

• Adjust inputs as desired, then press Start Streaming to watch how the AGI responds in real-time.

6. Summary

Your inputs act like dials on a complex machine — turning them changes how the AGI thinks, grows, and reacts.

By carefully tuning these inputs and watching the outputs, you can guide the system proactively, encouraging useful growth while avoiding runaway divergence or collapse.

If you want, I can help you build:

• Visual charts to track growth and decisions

• Exportable logs for offline analysis

• Alerts for when the system needs adjustment