Module: Legion::Extensions::Agentic::Self::Identity::Helpers::Dimensions

Defined in:
lib/legion/extensions/agentic/self/identity/helpers/dimensions.rb

Constant Summary collapse

IDENTITY_DIMENSIONS =

The 6 behavioral dimensions that constitute identity

%i[
  communication_cadence
  vocabulary_patterns
  emotional_response
  decision_patterns
  contextual_consistency
  temporal_patterns
].freeze
HIGH_ENTROPY_THRESHOLD =

Entropy thresholds (from tick-loop-spec Phase 4)

0.70
LOW_ENTROPY_THRESHOLD = 
0.20
OPTIMAL_ENTROPY_RANGE = 
(0.20..0.70)
OBSERVATION_ALPHA =

EMA alpha for dimension updates

0.1

Class Method Summary collapse

Class Method Details

.clamp(value, min = 0.0, max = 1.0) ⇒ Object 



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# File 'lib/legion/extensions/agentic/self/identity/helpers/dimensions.rb', line 66

def clamp(value, min = 0.0, max = 1.0)
  value.clamp(min, max)
end

.classify_entropy(entropy) ⇒ Object 



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# File 'lib/legion/extensions/agentic/self/identity/helpers/dimensions.rb', line 56

def classify_entropy(entropy)
  if entropy > HIGH_ENTROPY_THRESHOLD
    :high_entropy
  elsif entropy < LOW_ENTROPY_THRESHOLD
    :low_entropy
  else
    :normal
  end
end

.compute_entropy(observations, model) ⇒ Object 



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# File 'lib/legion/extensions/agentic/self/identity/helpers/dimensions.rb', line 36

def compute_entropy(observations, model)
  return 0.5 if observations.empty?

  divergences = IDENTITY_DIMENSIONS.filter_map do |dim|
    obs = observations[dim]
    next unless obs

    baseline = model[dim]
    next 0.0 unless baseline && baseline[:observations].positive?

    # Weighted divergence from established baseline
    (obs - baseline[:mean]).abs / [baseline[:variance].to_f, 0.1].max
  end

  return 0.5 if divergences.empty?

  raw = divergences.sum / divergences.size
  clamp(raw / 3.0) # normalize: divergence of 3.0 stddevs = entropy 1.0
end

.new_identity_model ⇒ Object 



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# File 'lib/legion/extensions/agentic/self/identity/helpers/dimensions.rb', line 30

def new_identity_model
  IDENTITY_DIMENSIONS.to_h do |dim|
    [dim, { mean: 0.5, variance: 0.1, observations: 0, last_observed: nil }]
  end
end