ai.13 · Scenario S3

Autonomous Agent Ensembles with Feedback Loops

Feedback loop instability in self-modifying agent ensembles with dense peer-to-peer observation and continuous autonomous adaptation.

Scenario Definition

System Class

Self-modifying agent ensembles where performance feedback influences future behavior through dense peer-to-peer observation and adaptation.

Scaling State

Feedback instability regime with oscillating behaviors, runaway adaptations, and collective behavioral divergence under dense coupling.

Operational Mode

Densely connected mesh with mutual observation, competitive selection for conflict resolution, and continuous autonomous adaptation.

Stability Dimension

Behavioral coherence — stable collective behavior patterns under continuous adaptation dynamics.

Recognition Pattern

Your agent ensemble shows periods of excellent performance followed by sudden degradation, with no clear trigger. Behaviors oscillate unpredictably, some agents develop increasingly extreme strategies, and collective behavior diverges from intended patterns despite no individual agent appearing broken.

Structural Observations

Findings derived from structural analysis of feedback dynamics and adaptation coupling in dense agent meshes.

Positive feedback loops through mutual observation amplify behavioral variations into runaway adaptations.
Competitive selection mechanisms under dense coupling produce oscillating rather than converging behaviors.
Collective behavioral drift emerges from individually rational adaptations to peer behavior.
Stability periods alternate with instability periods as feedback dynamics cross thresholds.

Stability Projection

Comparative stability classification before and after structural feedback stabilization intervention.

Baseline

Chaotic

Reserve: unpredictable

→

Comparison

Dampened

Reserve: bounded

Aggregated Metrics

Normalized indicators. Baseline values crossed out, comparison values highlighted.

Behavioral Stability Index

0.31 0.78

Oscillation Frequency

0.47 0.11

Runaway Adaptation Rate

0.38 0.08

Collective Coherence

0.29 0.81

Performance Variance

0.64 0.19

Predictability Horizon

0.22 0.73

Decision Implication

Primary insight: If your self-modifying agent ensemble shows alternating periods of excellent and degraded performance with no clear trigger, you have a structural feedback stability problem.

Monitoring limitation: Per-agent adaptation metrics show rational behavior while collective dynamics become chaotic.

Scaling consideration: Denser agent coupling or more frequent adaptation may exponentially increase instability risk.

Evidence & Artefacts

Pre-computed analysis outputs for this scenario.

ZIP Evidence Bundle (ai.13.S3) PDF Scenario Report

Such structural findings are typically contextualized through a scoped architecture risk assessment.