UA-HMC World Modelers Kickoff Demo

Welcome to the UA-HMC team's interactive assembly demo! This app processes text with the Eidos machine reader, extracts factors and the causal links between them, assembles an executable probabilistic model, and generates distributions of the values of the factors over multiple time steps.

Causal Analysis Graph


{% if state.histos_built %}
{% endif %}
{% if state.s0 != None %}

Simulable Factors

Enter the initial values for the factors, their time derivatives, and their standard deviations here, along with the number of sequences to sample and number of time steps to evolve the state over.

{% for k, v in state.s0.items() %}

{{ k }}

{% if not k.startswith('∂') %}

{{ 'σ'+k }}

{% endif %}
{% if not k.startswith('∂') %} {% endif %}
{% endfor %}

{% endif %}