lex-emotion

Multi-dimensional emotional valence system for brain-modeled agentic AI. Models emotional state across four dimensions, computes arousal and gut instinct signals, and modulates attention.

Overview

lex-emotion implements the agent's affective layer. Emotional state is not a single scalar — it is a four-dimensional valence vector. Valence influences memory decay rates, attention allocation, and gut instinct signals. Momentum (exponential moving average) smooths emotional state over time.

Valence Dimensions

Dimension	Description
urgency	Time pressure and immediacy
importance	Impact scope and outcome severity
novelty	Degree of unexpectedness
familiarity	How well-known the domain/source is

All dimensions are clamped to [0.0, 1.0].

Source Urgency Defaults

Source Type	Urgency Weight
firmware_violation	1.0
human_direct	0.9
mesh_priority	0.7
scheduled	0.4
ambient	0.1

Installation

Add to your Gemfile:

gem 'lex-emotion'

Usage

Evaluating Valence

require 'legion/extensions/emotion'

# Evaluate a signal's emotional valence
result = Legion::Extensions::Emotion::Runners::Valence.evaluate_valence(
  signal: { urgency_hint: 0.8, domain_weight: 0.9, impact_scope: 0.6,
            reversibility: 0.2, outcome_severity: 0.8 },
  source_type: :human_direct,
  deadline: Time.now.utc + 3600
)

result[:valence]            # => { urgency: 0.72, importance: 0.68, novelty: 0.5, familiarity: 0.0 }
result[:magnitude]          # => 1.09 (Euclidean norm)
result[:dominant_dimension] # => :urgency

Aggregating Multiple Valences

valences = [
  { urgency: 0.8, importance: 0.7, novelty: 0.4, familiarity: 0.3 },
  { urgency: 0.5, importance: 0.9, novelty: 0.2, familiarity: 0.6 }
]

Legion::Extensions::Emotion::Runners::Valence.aggregate_valences(valences: valences)
# => { aggregate: {...}, arousal: 0.65, dominant: :importance, count: 2 }

Gut Instinct

# Compressed parallel query — returns a signal classification
result = Legion::Extensions::Emotion::Runners::Gut.gut_instinct(
  valences: valences,
  memory_signals: [1, 2, 3],
  confidence_threshold: 0.5
)

result[:signal]     # => :alarm | :heightened | :explore | :attend | :calm | :neutral
result[:confidence] # => 0.0..1.0
result[:reliable]   # => true/false

Current Emotional State

Legion::Extensions::Emotion::Runners::Gut.emotional_state
# => { momentum: { valence_ema: {...}, arousal_ema: 0.4, stability: 0.9, history_size: 5 },
#      baseline: { urgency: {...}, ... } }

Attention Modulation

Legion::Extensions::Emotion::Runners::Valence.modulate_attention(
  base_salience: 0.5,
  valence: { urgency: 0.8, importance: 0.7, novelty: 0.3, familiarity: 0.5 }
)
# => { original: 0.5, modulated: 0.72, boost: 0.22 }

Momentum

Emotional momentum is an exponential moving average (alpha = 0.3) over valence and arousal. It tracks valence_ema, arousal_ema, stability, and last 100 data points.

Actors

Actor	Interval	Description
MomentumDecay	Every 60s	Periodically drifts emotional momentum toward neutral valence via exponential decay, preventing permanent extreme states

Development

bundle install
bundle exec rspec
bundle exec rubocop

License

MIT