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Observation Contexts

An Observation Context is a set of beliefs that are grouped together based on how the Self-Model perceives the world. For example, if a Self-Model is tracking their sleep and heart rate variability, they might create an Observation Context for “Sleep and Heart Rate Variability”.

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Creating an Observation Context

observation_context = epistemic_me.ObservationContext.create(
    self_model_id="self_001",
    name="Sleep and Heart Rate Variability",
    possible_values=[
        {"sleep_min": 0},
        {"sleep_max": 16},
        {"hrv_min": 0},
        {"hrv_max": 150}
    ],
    context="sleep_and_hrv"
)

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Working with Observation Contexts

Observation Contexts can be used to:
  • Group related beliefs together
  • Provide context for falsifiable and causal beliefs
  • Define possible values for observations
  • Track historical observations and evidence

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Conceptualized Belief Systems

When working with Observation Contexts, you can create a Conceptualized Belief System that forms a graph data structure representing an ontology of a Self-Model: 
belief_system = epistemic_me.SelfModel.retrieve_belief_system(
   id="self_001",
   conceptualize=True
)