Agent Metrics

Observing agent behavior without collapsing cognition into numbers#

Agent metrics in EcoEchoSystem are diagnostic signals, not truth claims.
They exist to surface patterns, stress, and transitions — not to rank agents or predict outcomes.

Metrics are windows, not controls.

Purpose#

This module exists to:

define observable indicators of agent state and behavior
support comparative analysis across runs
detect stress, misalignment, and transition pressure
inform interpretation without enforcing optimization
prevent metric‑driven distortion of cognition

Metrics must illuminate without dictating.

Metrics as Substrate Expression (S / E / R)#

Structure (S)#

role stability
network position
institutional embedding
memory depth

Activation (E)#

stress load
conflict exposure
persuasion intensity
urgency signals

Relational Time (R)#

learning lag
trust half‑life
identity inertia
correction latency

Metrics track movement through time, not static state.

Metric Categories#

1. Cognitive State Metrics#

Indicators of internal condition:

attention saturation
belief coherence
confidence‑accuracy divergence
narrative stability

Used to detect mislearning and overload.

2. Identity Metrics#

Indicators of identity health:

identity coherence score
boundary rigidity
value conflict frequency
transition pressure index

Used to anticipate identity transitions.

3. Learning Metrics#

Indicators of adaptation:

learning rate
error persistence
transfer effectiveness
forgetting rate

Used to distinguish adaptation from illusion.

Indicators of relational dynamics:

trust density
influence centrality
coordination success rate
polarization index

Used to assess collective viability.

5. Behavioral Metrics#

Indicators of action patterns:

action diversity
habit dominance
exploration vs exploitation ratio
response latency

Used to detect rigidity or panic.

Metric Interpretation Rules#

Metrics must be:

interpreted comparatively
contextualized historically
read alongside qualitative artifacts

No metric is meaningful in isolation.

Metric Guardrails#

Agent metrics must never:

define success or failure
drive agent decision logic
collapse uncertainty
replace human interpretation

Metrics are for observers, not agents.

Failure Modes#

Metric systems fail when:

agents optimize for metrics
metrics become goals
observers mistake signal for cause
dashboards replace understanding

Good metrics resist gamification.

Integration Notes#

Agent metrics:

observe the agent loop
surface identity and learning stress
inform guided exploration
support educational and foresight labs

This module completes the cognitive observability layer.

Status#

Canonical agent metrics framework for cognitive agent simulation.
Designed for analysis, interpretation, and epistemic restraint.