autodynamics 0.1.0a1

Modelling autonomy dynamics over the Autonometrics atlas. Ships ProfileTrajectory: a recording substrate for sequences of autonomy profiles. Layer 2 of the Autonometrics -> Autodynamics -> Ex-Machina trilogy.

Autodynamics

Layer 2 of 3 in the autonomy research trilogy: Autonometrics (measure) -> Autodynamics (explain) -> Ex-Machina (build / emulate)

Status: Pre-alpha. Ships a recording substrate; no stable theoretical model yet.

Vision

Autonometrics quantifies where a system sits on the five autonomy axes (closure, memory, constraint closure, persistence, coherence). Autodynamics aims to model how systems move across that atlas: trajectories, attractors, transitions, and the dynamical regularities that govern changes in autonomy.

This package will eventually expose:

• Trajectory analysis tools over AutonomyProfile time series.
• Phase-space modelling for systems described by the AutonomySystem protocol.
• Stability and attractor characterisation across the five-axis atlas.
• Hooks for empirical validation against longitudinal data from biology, AI, and motivational psychology corpora.

What this package contains today

A minimal recording substrate: ProfileTrajectory. A class that:

1. Stores a sequence of AutonomyProfile values measured at successive moments.
2. Exposes axis-wise time series for any of the five canonical axes.
3. Computes pairwise consecutive deltas.
4. Sums the resulting magnitudes into a total path length in profile space.

It is the smallest piece of code that lets you treat a sequence of autonomy measurements as a trajectory in a metric space — the precondition for any later dynamical analysis.

Install with: pip install autodynamics Import as: import autodynamics

Quick run

pip install autodynamics
autodynamics-demo --n-states-list 3 4 5 6 8 --n-steps 600

You will see a small table of (closure, memory) profiles measured over a sweep of SimpleAutomaton configurations, the consecutive deltas between them, and the total path length.

Toy demo: ProfileTrajectory

Disclaimer. This is the recording substrate of Autodynamics, not its theory. The trajectory class lets you collect, traverse, and compute simple geometric quantities over a sequence of AutonomyProfiles. It does not interpret what those movements mean — that interpretation is the open research question this package will eventually try to answer. Treat the code as a useful template, not as evidence.

import autonometrics as anm
from autodynamics import ProfileTrajectory

trajectory = ProfileTrajectory(axes=("closure", "memory"))

for n_states in [3, 4, 5, 6, 8]:
    sys = anm.SimpleAutomaton.demo(n_states=n_states, n_steps=600)
    sys.run()
    profile = anm.measure(sys, axes=["closure", "memory"])
    trajectory.append(profile)

print(trajectory.axis_series("closure"))    # time series of one axis
print(trajectory.deltas())                  # pairwise consecutive movements
print(trajectory.total_path_length())       # sum of delta magnitudes

Roadmap

• v0.1.0a1 (current): Toy trajectory recorder. Reserves name, declares vision, ships demo.
• v0.2.x: First serious dynamics primitives (attractor characterisation, regime classification). Lands after Autonometrics reaches v1.0.
• v1.0.0: Stable trajectory API on top of Autonometrics profiles.

Position in the trilogy

Layer	Project	Question it answers
1	Autonometrics	Where does a system sit on the autonomy atlas?
2	Autodynamics	How does it move across the atlas over time?
3	Ex-Machina	Can we build a system that occupies a chosen region?

License

Apache License 2.0 — see LICENSE.

Citation

If you reference this work, please cite Autodynamics directly. A formal citation block will be added in v0.2.x.